AI Engineering Manager

• 8-10 years of experience in data engineering and architecture roles, with 2+ years in an engineering leadership role. • Strong experience leading ML/AI engineering efforts from concept through production in fast‑moving organizations. • Exposure to Databricks, Mosaic AI Gateway, and related Data + AI technologies. • Working knowledge of RAG architectures, SQL Agents, and MCP. • Strong analytical and problem‑solving skills, with the ability to translate complex problems into clear execution plans. • Proven ability to mentor and coach less‑experienced engineers, providing technical guidance, feedback, and growth support across complex AI initiatives. • Acts as a technical mentor across teams, elevating engineering quality by developing junior engineers and modeling best practices in AI system design and delivery. • Compensation: Compensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants. • What you’ll get in return: • Unlimited paid time off – recharge when you need it • Work from anywhere – flexibility to fit your life • Comprehensive health coverage – multiple plan options to choose from • Equity for every employee – share in our success • Growth-focused environment – your development matters here • Monthly cell phone allowance – stay connected with ease #LI-SB1 #LI-Remote • Bachelor’s degree in computer science, Information Systems, Data Analytics, or a related field, or equivalent experience. • 2-4 years of hands‑on experience in BI development and dashboard creation. • Proficiency with Power BI Desktop, Power BI Service, and Power BI Fabric. • Ability to leverage GenAI features in Power BI (Copilot, AI visuals, natural language queries). • Solid understanding of Power BI security, including RLS and permission management. • Strong analytical thinking, problem‑solving, and teamwork skills. • Skilled in data modeling and Power Query transformations. • Working knowledge of SQL and relational database concepts. • High attention to detail with strong troubleshooting ability. • Effective communication skills for working with cross‑functional stakeholders. • What we would like to see, but not required • Knowledge of workspace governance, deployment pipelines, and version control (Git). • Exposure to ETL tools. • What you’ll get in return • Bachelor’s Degree in Marketing, Communications, Business, or related field, or relevant equivalent work experience. • Minimum 2 years of professional experience in branding, marketing or digital media creation. • Experience with photography and video creation for branding or marketing. • Proficiency with social media, design tools and digital marketing software (e.g., Adobe Creative Suite, Canva, HubSpot, etc.). • Exceptional communication, storytelling, and presentation skills with the ability to tailor messaging to different audiences. • Self-starter with the ability to work independently and collaborate effectively with cross-functional team members across India, Nepal and US to drive toward action. • Knowledge of SEO and website analytics • Experience/interest in AI process improvement and automation • Bachelor’s or master’s degree in computer science, Information Technology, Data Analytics, or a related field with 3 - 5 years of relevant experience • Strong data analysis, problem‑solving, and logical thinking skills. • Advanced SQL expertise, including complex queries and stored procedures. • Ability to gather requirements, clarify needs, and translate them into clear analytical tasks. • Comfort working with multiple data sources and understanding data modelling basics. • Good communication and documentation skills with a collaborative mindset. • Moderate familiarity with Power BI and data integration concepts. • Basic DAX or M Query knowledge • Understanding of ETL tools or cloud platforms (Azure/AWS/GCP) • Bachelor’s or master’s degree in computer science, Information Technology, Data Analytics, or a related field with 3 - 5 years of relevant experience in data analysis/BI. • Strong analytical and problem‑solving skills help turn raw data into clear, actionable insights. • Advanced SQL expertise that ensures the business has fast, accurate, and trustworthy data. • Experience with Power BI data modelling that supports reliable, high‑quality dashboards. • Confidence working with multiple data sources to create a complete, consistent view of the business. • Clear communication and documentation skills that make complex findings easy to understand. • A collaborative approach that helps translate business needs into meaningful analytical solutions. • Exposure to DAX, M Query, or basic ETL tools • Understanding of cloud data ecosystems (Azure, AWS, or GCP) • Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field. • 3+ years of hands‑on experience as a Data Engineer working with distributed data processing systems in modern cloud environments. • Working knowledge of U.S. healthcare data domains — including claims, eligibility, and provider datasets — and ability to apply this knowledge to ingestion and transformation workflows. • Strong communication skills to articulate technical concepts across both technical and non‑technical stakeholders. • Proficiency in Python, SQL, and PySpark, including distributed data transformations and performance‑optimized queries. • Demonstrated experience building and operating production ETL/ELT pipelines using Databricks, Airflow, or similar orchestration frameworks. • Familiarity with cloud‑native data platforms and services such as dbt, Kafka, Delta Lake, and event‑driven/streaming architectures. • Experience with structured and semi‑structured data formats (Parquet, JSON, Avro, ORC), including schema evolution techniques. • Working knowledge of AWS data ecosystem components—S3, SQS, Lambda, Glue, IAM—used to support scalable data engineering workloads. • Experience with Terraform and modern CI/CD pipelines (e.g., GitLab) for automating deployment and versioning. • Understanding of SQL optimization strategies including partitioning, pruning, Z‑Ordering, clustering, and caching for large analytical workloads. • Experience using cloud data warehouse technologies such as Snowflake, BigQuery, or Redshift, including performance tuning and data modeling practices. • What we would like to see but not required: • Experience in healthcare or payer data environments at scale. • 3-5 years of experience in product management, including product strategy execution, data analytics, agile delivery, and relevant technologies and tools. • Strong knowledge of US healthcare payer data, payer operations and/or analytics, and experience across Medicare, Medicaid, Marketplace, and Commercial insurance programs. • Hands‑on experience with payment integrity pre‑pay and post‑pay approaches, including relevant datasets such as claims, provider, member, enrollment, contracts/fee schedules, and clinical or adjustment notes. • Experience applying advanced analytics and/or AI to operational or analytical payment integrity use cases • Excellent written and verbal communication skills with the ability to clearly explain complex concepts, influence stakeholders, and tell a compelling product story. • Demonstrated ability to lead cross‑functional teams and coordinate efforts across multiple roles to achieve product objectives. • Proven ability to independently drive workstreams, lead through influence, manage risk, and escalate issues appropriately. • Comfort operating in a fast‑paced, evolving startup environment. • Bachelors Degree in a relevant field (e.g., Data Science, Business Administration, Healthcare Management) or equivalent relevant professional experience. • Relevant certifications (e.g., Product Management, Data Analytics, Scrum Product Owner) • Experience with analytics and visualization tools (SQL, Power BI, Tableau) • Familiarity with Agile methodologies and product management tools • Monthly cell phone allowance – stay connected with ease #LI-RF1 #LI-Remote • Proven experience managing engineering teams in data-driven environments. • Strong technical background in distributed systems, data platforms, and cloud infrastructure. • Excellent communication, leadership, and organizational skills. • Familiarity with agile methodologies and cross-functional collaboration. • Experience with US healthcare data analysis. • What we would like to see, but not required: • Hands-on experience with Databricks, Snowflake, SQL, PySpark. • Knowledge of Git, CI/CD pipelines. • Exposure to cloud platforms like Azure or AWS. • Working Conditions: • Standard hours: 8 hours/day, 10 AM - 7 PM • Location: Onsite • At least 7 years in data engineering roles with experience in leading high performing teams. • Deep technical expertise in data engineering, distributed systems, and software architecture. • Proven experience mentoring and developing engineering talent. • Strong track record in defining and enforcing engineering best practices. • Ability to lead cross-functional collaboration and communicate effectively with diverse stakeholders. • Experience managing technical projects from planning through production handover. • Fluency in English (required for Nepal and India). • Commitment to continuous learning and staying current with industry trends. • Experience driving innovation and continuous improvement in engineering processes. • Familiarity with cloud services and modern deployment workflows. • Ability to foster a culture of experimentation and excellence. • Prior experience coordinating resource allocation across multiple engineering streams. • Working Conditions (Nepal Only) • Standard hours: 9 hours/day; 5 days/week • Location: On-Site • 10+ years of experience in software engineering, SRE, sustaining engineering, or production operations • Deep hands-on experience operating production systems in AWS • Strong experience troubleshooting Databricks and large-scale data platforms • Proficiency in Python and experience building production services or tooling • Strong understanding of: • Distributed systems • Incident management and RCA practices • Monitoring, alerting, and observability • CI/CD Pipelines that leverage Infrastructure as Code. • Proven ability to own problems end-to-end, from detection to permanent resolution • Excellent communication skills, especially during incidents and customer escalations • Ability to work backward from customer impact to root cause across systems and codebases, delivering fixes in environments with minimal documentation. • Strong instinct for operational risk, with the ability to proactively identify failure modes and harden systems before they impact customers. • Experience in healthcare, health insurance, or regulated data environments • Familiarity with: • Kubernetes (EKS), EMR, Lambda • Spark internals • Snowflake or similar data warehouses • Experience with FHIR, MDM systems, or entity resolution • Prior experience in SWAT, escalation engineering, or tiger-team roles • Experience contributing to or operating within SRE/on-call programs • Monthly cell phone allowance – stay connected with ease#LI-MS1 • · Bachelor's degree in Computer Science, Engineering, Business, or related field. • · Exceptional Product Mangament acccumen in a related field - a minimum of 8 years of total experience, with 5-6 years of product management experience leading cloud-native B2B infrastructure and interoperability solutions. • · Expertise in leading and expanding cloud infrastructure capabilities of Enterprise solutions hosted in AWS and Azure. Experience with GCP is a plus. • · Proven experience developing interoperability solutions processing HL7 V2 and FHIR and other healthcare focused message standards, such as X12. • · Industry experience leveraging Snowflake, Airbyte, Databrciks and other leading cloud technologies to develop highly scalable data solutions. • · Strong technical background with the ability to understand complex software and cloud infrastructure systems in close collaboration with Engineering, SecOps and CloudOps. • · Hands-on experience with evangelizing and applying Agile development methodologies. • · Previous experience working with US teams and proven track record of successful and on-time delivery working in an international orgnization. • · Exceptional communication and leadership skills, with the ability to articulate complex concepts to diverse audiences. • · Exceptionally strong client acumen with the ability to effectively communicate product roadmap while listening empathetically to understand client needs to solve them holistically. • · Strong analytical skills, with the ability to leverage data to drive product decisions. • · Strong project management skills and experience collaborating with Client Delivery to ensure on-time and on-budget delivery of committed features and solutions. • · Demonstrated ability to thrive in a fast-paced, dynamic startup-like environment. • · Experience working in an Enterprise Healthcare IT field, specifically US Healthcare Payers. • · Demonstrable experience in improving operational efficiencies and leading CI/CD process optimization initiatives. • · Operational expertise leveraging GenAI to solve business problems with a detailed understanding of how compound AI systems function. • Bachelor’s Degree (or equivalent) and/or Professional Certification(s) in Marketing, Business, and/or relevant creative services • 5+ years of professional experience in product marketing, including developing and executing data-driven, multi-channel marketing initiatives and campaigns. • 3+ years of experience in the US healthcare and/or Health IT industry. • Experience in Design, Creative Services, and/or Copy Editing with the ability to showcase sample marketing materials and/or creative services content. • Proficiency with design tools and digital marketing software (e.g., Adobe Creative Suite, Canva, HubSpot, etc.). • Self-starter with the ability to work independently and collaborate effectively with cross-functional team members to drive toward action. • Process driven with high attention to detail and strong organization; consistent on deadlines, documentation, and tracker hygiene • Experience marketing healthcare technology/SaaS products to U.S. healthcare payers • Familiarity with U.S. healthcare payer program areas - Payment Integrity, Total Cost of Care, Interoperability, Risk adjustment, or Utilization management • Technical and/or B2B product marketing experience. • Proficiency with data analysis tools for campaign performance tracking. • Experience/interest in AI process improvement/workflow optimization enablement for product marketing • A deep understanding of data software engineering or a minimum of 3 years of software development or data engineering experience. • Domain expertise in shipping Software as a Service (SaaS) products. • Deep domain expertise in cloud technologies, including AWS, Azure and/or GCP. • Skilled in database concepts and tools (preferably on Databricks and Snowflake). • Deep understanding of the data platform R&D processes and agile methodologies. • Experience with big data, ETL and data pipelines, security and privacy, DevOps, or automation. • BS or MS in Computer Science, or related fields, or equivalent experience in a technical product owner role or an adjacent position. • Proven ability to influence and coordinate cross-functional teams to execute plans in highly technical environments. • Exceptional communication skills critical for translating business requirements into technical specifications, and communicating with technical and non-technical audiences. • Well-developed strategic-thinking skills, with the ability to inspire and lead others. • A highly proactive get it done attitude and the skills to back it up. • Demonstrated ability to thrive in a fast-paced, dynamic startup environment. • US Healthcare Payor or Provider industry experience. • Experience with healthcare interoperability standards such as HL7 V2, FHIR and X12. • Experience with integrating or implementing healthcare-related EMPI/MDM workflows. • Coach and mentor software and AI developers, develop staff skills, provide continuous feedback • Has relentlessly high standards (is never satisfied with the status quo) • Responsible for protecting, securing, and proper handling of all confidential data held by Abacus to ensure against unauthorized access, improper transmission, and/or unapproved disclosure of information that could result in harm to Abacus or our clients. • Minimum of 3 years of ML/AI engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML/AI research in academia will be considered as contributing qualification • Minimum of 3 years of experience as a software developer at some point in career • Minimum of 2 years of experience with Databricks, Mosaic AI Gateway and associated technologies in Databricks stack related to Data and AI engineering • Strong track record of working with language modeling technologies and GenAI. This could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, evaluation benchmarks, Agents and Agentic workflows (e.g. orchestration, workflow management, observability, debugging), RAG, SQL Agents, MCP, etc. • Proficiency in Python, TensorFlow/PyTorch, and scalable ML/AI architecture • Ability to drive end-to-end model and system development, from research and prototyping to deployment and monitoring • Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences • Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment • Experience and good understanding of designing scalable, distributed systems for running small to medium scale data processing applications and services (10s – 100s of TBs of data) • Possesses a level of breadth and depth of software and AI development experience that allows for influence and competence in technical discussions with internal and external stakeholders • Solid understanding of roles adjacent to the software development (product management, project management, client delivery, operations etc.). Ability to adapt to these roles as defined at Abacus and work with others in these roles • Proven record of success of driving and/or leading engineering teams/projects towards developing production grade systems supporting customers • Nice to have experience with, but not required: Snowflake, FHIR, Healthcare Data exposure • Bachelor’s degree in Computer Science, or related field, or equivalent work experience. • Strong ability to enhance relationships with clients and internal teams. • Demonstrated multitasking abilities and responsiveness to priority changes. • Superior communication skills for engaging various stakeholders. • Extensive experience in gathering requirements and delivering effective solutions. • Leadership skills in process improvement and project execution. • Proven leadership, exceptional organizational skills, self-motivation, and a track record of successfully managing complex projects and client relationships while delivering innovative, market-leading solutions. • Working Conditions • Standard hours: 8 hours/day, 5 days/week • Location: On-site. • Work time:1 PM - 10 PM • 5+ years of hands‑on experience as a Data Engineer working with large‑scale, distributed data processing systems in modern cloud environments. • Working knowledge of U.S. healthcare data domains—including claims, eligibility, and provider datasets—and experience applying this knowledge to complex ingestion and transformation workflows. • Strong ability to communicate complex technical concepts clearly across both technical and non‑technical stakeholders. • Expert‑level proficiency in Python, SQL, and PySpark, including developing distributed data transformations and performance‑optimized queries. • Demonstrated experience designing, building, and operating production‑grade ETL/ELT pipelines using Databricks, Airflow, or similar orchestration and workflow automation tools. • Proven experience architecting or operating large‑scale data platforms using dbt, Kafka, Delta Lake, and event‑driven/streaming architectures, within a cloud‑native data services or platform engineering environment—requiring specialized knowledge of distributed systems, scalable data pipelines, and cloud‑scale data processing. • Experience working with structured and semi‑structured data formats such as Parquet, ORC, JSON, and Avro, including schema evolution and optimization techniques. • Strong working knowledge of AWS data ecosystem components—including S3, SQS, Lambda, Glue, IAM—or equivalent cloud technologies supporting high‑volume data engineering workloads. • Proficiency with Terraform, infrastructure‑as‑code methodologies, and modern CI/CD pipelines (e.g., GitLab) supporting automated deployment and versioning of data systems. • Deep expertise in SQL and compute optimization strategies, including Z‑Ordering, clustering, partitioning, pruning, and caching for large‑scale analytical and operational workloads. • Hands‑on experience with major cloud data warehouse platforms such as Snowflake (preferred), BigQuery, or Redshift, including performance tuning and data modeling for analytical environments. • Experience in large-scale healthcare or payer data environments. • 8+ years of experience in data modeling, enterprise data architecture, and cloud-based data engineering. • 4+ years leading data modeling teams in enterprise environments. • Expertise in enterprise data modeling tools (Erwin, ER/Studio, DBSchema, or similar). • Strong hands-on experience with cloud data platforms (Databricks, Snowflake) and data lakehouse architectures. • Deep understanding of healthcare data models across Core Payer (Claims, Membership, Enrollment, Provider, Billing, Premium) and Clinical Interoperability (FHIR, HL7, ADT, CCDA, etc.) domains. • Experience with schema evolution, lossless data modeling, and data versioning strategies. • Strong background in SQL, performance tuning, and query optimization for large-scale datasets. • Hands-on experience with data engineering workflows, including data pipeline integration, ELT/ETL optimizations, and data transformation frameworks. • Ability to mentor junior modelers, enforce modeling best practices, and drive adoption of enterprise data standards. • Excellent collaboration skills to work with data architects, engineers, and client implementation teams. • Experience with OBT, data Lakehouse, and metadata management frameworks. • Familiarity with business intelligence (BI) and reporting solutions on modern cloud data warehouses. • Knowledge of APIs, SDKs, and data distribution frameworks for enabling real-time and batch data access. • Experience with data governance, security, and regulatory compliance in healthcare data management. • 5+ years in Quality Assurance for software platforms, preferably cloud systems. • 2+ years in software development. • 2+ years working with FHIR databases and standards, including FHIR API testing. • Strong understanding of Software Lifecycle and QA processes for manual and automated testing. • Expertise in Azure and AWS platforms. • Knowledge of healthcare standards. • Data QA validation and strong analytical skills • Knowledge of Medallion architecture and hands-on experience with Databricks • Excellent analytical, problem-solving, and troubleshooting skills. • Creating and maintaining frameworks using pytest, JUnit, or similar. • Database systems (MongoDB, SQL, MySQL) and data validation. • Microservices architecture, container management, API gateways, and tools like Kubernetes. • Coach and mentor software developers, develop staff skills, provide continuous feedback (i.e. one on ones) and are responsible for annual reviews. • Innovation and outside the box thinking • Has passion and conviction and the innate ability to inspire passion in others • Minimum of 5 years of software development experience using cloud services in production environment (AWS, Azure, GCP, etc) • Minimum of 2 years of experience with Data Lakehouse, ideally Databricks. SQL and Python query experience • Experience building production solutions on top of data systems at scale • Experience working with FHIR standards and FHIR databases preferred • Ability to drive end-to-end development, from research and prototyping to deployment and monitoring • Strong analytical and problem-solving skills, with a passion for improving UI/UX-driven user experiences • Strong coding and software engineering skills, and familiarity with software engineering principles around testing, debugging, code reviews and deployment • Possesses a level of breadth and depth of software and UI/UX development experience that allows for influence and competence in technical discussions with internal and external stakeholders • Proven record of success of driving projects towards delivering production grade systems supporting customers • Bachelor’s degree in computer science, Engineering, Information Technology, or related field, with 2+ years of hands‑on experience in Data QA or Data Engineering QA • Strong expertise in SQL, including complex queries, joins, aggregations, performance optimization, and data validation • Working knowledge of Python for data analysis, synthetic data creation, and automation of QA processes • Proven ability to analyze large datasets, identify inconsistencies, and validate business logic • Solid understanding of QA methodologies with experience designing test cases for data‑centric systems • Experience with PySpark, Databricks, and AWS services such as Redshift, S3, and Athena; familiarity with analytics and reporting tools is a plus • Experience with BigQuery, Snowflake, and ETL test automation • Healthcare domain knowledge, including HEDIS quality measures • Understanding and passion for healthcare data and systems – including payer, provider, and integration partners. Strong working knowledge of US healthcare data, including but not limited to Medical Claims, Pharmacy Claims, Membership / Enrollment, Provider and Clinical. • Domain expertise in CMS Interoperability Mandate (9115 / 0057) - including the technology used to serve the mandated APIs as well as the data structures (FHIR) required to be compliant. • Ability to define the solution architecture vision in architecture design documents • Broad and general technical knowledge as well as competencies in infrastructure, data models, databases, service orientation, programming, frameworks, standards, and technical modeling. Strong experience with one or more cloud vendors (AWS / Azure / GCP) and data platforms (Databricks / Snowflake) desired. • Strong understanding of healthcare industry trends, regulations, and customer needs with preference for previous payer / Interoperability vendor experience • Experience translating business needs into technology solutions that enable delivery of the Abacus platform. • Strong communicator who can leverage their domain and technical expertise effectively with the client and build working relationships with internal and external team members. Ability to communicate succinctly and clearly, both verbally and written, across technical and non-technical audiences at multiple levels, including business leaders. • Experience working in the payer / healthcare data space and understanding of the historical data architecture needs of our clients. • Understanding of client services or experience working for a cloud-based data management provider to large clients. • Working knowledge of Provider (EHR) Data formats and topics – including FHIR, X-12, HL-7 V2.3, and CCDA/CDA - as well as the general system architecture required to consume and make use of this data. • Working knowledge of Utilization Management / Care Management / Disease Management. • Monthly cell phone allowance – stay connected with ease • 7+ years of hands‑on experience as a Data Engineer working with large‑scale, distributed data processing systems in modern cloud environments. • Proven experience hiring top-tier talent in competitive markets (we’d love to see ~4+ years, but impact matters more than years). • Experience running full-cycle recruiting, including sourcing strategy, stakeholder management, and closing. • Strong ability to manage high-complexity searches with many moving parts — you stay structured, adaptable, and focused. • Skilled at translating technical and business needs into clear hiring strategies and compelling candidate narratives. • Excellent written and verbal communication — you build trust with both deeply technical candidates and senior stakeholders. • Comfortable operating in fast-paced, remote-first environments and collaborating across global time zones. • Experience recruiting globally across multiple regions. • Background in high-growth startups or similarly fast-moving environments. • A builder’s mindset: you experiment, learn quickly, spot patterns, and continuously refine recruiting playbooks and processes.