About the role

We are seeking an accomplished Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work directly with customers, data vendors, and internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment.

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will guide customers in adopting Abacus’s core data management platform and ensure high-quality, compliant data operations across the lifecycle.

Your day to day

• Architect, design, and implement high-volume batch and real-time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating with Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor data APIs, ensuring data quality, lineage, and schema evolution.
• Develop data modeling frameworks, including star/snowflake schemas and optimization techniques for analytical workloads on cloud data warehouses.
• Lead technical solution design for health plan clients, creating highly available, fault-tolerant architectures across multi-account AWS environments.
• Translate complex business requirements into detailed technical specifications, engineering artifacts, and reusable components.
• Implement security automation, including RBAC, encryption at rest/in transit, PHI handling, tokenization, auditing, and compliance with HIPAA and SOC 2 frameworks.
• Establish and enforce data engineering best practices, such as CI/CD for data pipelines, code versioning, automated testing, orchestration, logging, and observability patterns.
• Conduct performance profiling and optimize compute costs, cluster configurations, partitions, indexing, and caching strategies across Databricks and Snowflake environments.
• Produce high-quality technical documentation including runbooks, architecture diagrams, and operational standards.
• Mentor junior engineers through technical reviews, coaching, and training sessions for both internal teams and clients.

What you bring to the team

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field.
• 7+ 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.

What we would like to see but not required:

• Experience in large-scale healthcare or payer data environments.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the role

We are seeking an accomplished Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work directly with customers, data vendors, and internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment.

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will guide customers in adopting Abacus’s core data management platform and ensure high-quality, compliant data operations across the lifecycle.

Your day to day :

• Architect, design, and implement high-volume batch and real-time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating with Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor data APIs, ensuring data quality, lineage, and schema evolution.
• Develop data modeling frameworks, including star/snowflake schemas and optimization techniques for analytical workloads on cloud data warehouses.
• Lead technical solution design for health plan clients, creating highly available, fault-tolerant architectures across multi-account AWS environments.
• Translate complex business requirements into detailed technical specifications, engineering artifacts, and reusable components.
• Implement security automation, including RBAC, encryption at rest/in transit, PHI handling, tokenization, auditing, and compliance with HIPAA and SOC 2 frameworks.
• Establish and enforce data engineering best practices, such as CI/CD for data pipelines, code versioning, automated testing, orchestration, logging, and observability patterns.
• Conduct performance profiling and optimize compute costs, cluster configurations, partitions, indexing, and caching strategies across Databricks and Snowflake environments.
• Produce high-quality technical documentation including runbooks, architecture diagrams, and operational standards.
• Mentor junior engineers through technical reviews, coaching, and training sessions for both internal teams and clients.

What you bring to the team :

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field.
• 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.

What we would like to see but not required:

• Experience in large-scale healthcare or payer data environments.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role

We are looking for a Data Modeler to join a global data modeling team responsible for transforming business requirements into conceptual and logical data models. This role requires understanding of healthcare data domains (Claims, Membership, Enrollment, Provider, Billing, Interoperability - FHIR, HL7, ADT, CCDA, etc.) and experience in enterprise data modeling best practices.

The Data Modeler will work closely with the Director of Data Modeling and Senior Data Modelers to adhere to data modeling standards, metadata governance, and follow data architecture strategies that align with business and technical needs. They will also collaborate with business analysts, product analysts, client implementation teams, and data governance teams to ensure models support operational and analytical use cases, high performance, and data integrity.

This is an exciting opportunity for a data modeler with experience in Databricks, Snowflake, schema evolution, and modern data engineering practices to shape the future of healthcare data platforms.

Your day to day

Identify and define requirements for canonical data models as well as consumption use cases required by enterprise healthcare customers. Your activities will include:

• Perform data profiling analysis.
• Use SQL, data modeling and data integrity principles.
• Build conceptual and logical data models aligned with enterprise architecture, business requirements and industry standards.
• Follow data modeling best practices, including schema evolution, lossless data modeling, metadata management, and data versioning.
• Use enterprise data modeling tools (Erwin, ER/Studio, DBT, or similar).
• Ensure models support analytical (data science, actuarial, reporting) and operational (Claims, Care Management) use cases.
• Maintain metadata, business glossary, entity relationship diagrams and data dictionaries to support data lineage and governance.
• Partner with Client Management, Product, and Business Analyst teams to understand client needs, assess data model impact, and ensure data models and related artifacts meet or exceed expectations.
• Work with client management teams to provide support and data model expertise during client implementation.

What you bring to the team

• 2+ years of experience in data modeling, enterprise data architecture, and cloud-based data engineering.
• Expertise in enterprise data modeling tools (Erwin, ER/Studio, DBSchema, or similar).
• NoSQL data model experience.
• 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, data profiling, and metadata creation and maintenance.
• Ability to learn from senior 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.

What we would like to see, but not required

• Healthcare reporting experience.
• 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.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role

We are seeking a Data Governance & AI Trust Manager to define and operationalize the governance framework that enables high‑quality, well‑governed data to safely and effectively power GenAI agents, copilots, and analytics across the company.

As the organization accelerates adoption of Generative AI, the quality, structure, provenance, and clarity of corporate operating data have become critical enablers of AI performance, trustworthiness, and value. This role exists to ensure that the company’s operating data ecosystem is intentionally designed, consistently governed, and fit for AI‑enabled use cases, rather than fragmented, ambiguous, or ad‑hoc.

This role reports to the CISO & CIO and operates as a cross‑functional data governance authority across all company content. It does not own or manage the data itself; content ownership remains with business and platform owners. Instead, this role defines the standards, policies, and operating expectations under which data is created, managed, shared, retained, and made eligible for analytics and GenAI use.

A core responsibility of the role is to set the vision for the company’s internal data ecosystem—including how platforms such as SharePoint, Confluence, Jira, Slack, Teams, and related systems should be used together—and to establish clear operational standards (for example, when content belongs in SharePoint versus Confluence, and how that decision impacts AI use).

Governance is expected to be operationalized through native platform controls and existing enterprise tooling, rather than through standalone or heavyweight governance systems. The role translates governance principles into practical, enforceable standards that improve data quality, reduce ambiguity, and materially improve GenAI outcomes.

This is not a traditional data engineering or compliance analyst role. Success requires strong program ownership, the ability to drive cross‑functional alignment without direct authority, and sound judgment at the intersection of data quality, AI trust, security, and business operations.

Your Day‑to‑Day

Governance Framework Design & Ownership

• Own and evolve the company’s Corporate Operating Data Governance framework
• Define governance standards for unstructured and semi‑structured data across collaboration and productivity platforms
• Establish clear ownership models (Data Owners, Data Stewards, Custodians) for operating data domains
• Ensure governance practices enable business velocity rather than obstruct it
• Operationalize governance through native platform capabilities (e.g., metadata, permissions, retention, labeling, workflows) rather than standalone governance tooling

Metadata, Classification & AI Eligibility

• Define and maintain metadata standards, including:
  • Data classification
  • Purpose of use
  • Lifecycle state
  • AI eligibility and exclusion rules
• Partner with Security and Legal to ensure alignment with privacy, regulatory, and contractual obligations
• Embed metadata and classification standards directly into existing platforms rather than creating parallel systems

Data Quality & Trustworthiness

• Establish fitness‑for‑purpose data quality expectations for corporate operating data
• Define quality signals for:
  • Accuracy
  • Completeness
  • Timeliness
  • Consistency
• Partner with business teams to identify high‑risk or high‑impact data domains
• Ensure AI‑enabled experiences are grounded in authoritative, explainable, and traceable data sources

Lifecycle, Retention & Risk Management

• Define lifecycle expectations for operating data, including creation, maintenance, archival, and deletion
• Coordinate retention and defensibility standards to support legal, compliance, and audit needs
• Reduce long‑term risk from unmanaged or over‑retained unstructured data
• Support eDiscovery and investigation readiness through clarity and traceability

Cross‑Functional Execution & Enablement

• Drive accountability across Product, Engineering, Security, Legal, IT, and Business teams
• Establish practical governance cadences, reporting, and decision forums
• Provide authoritative guidance and operating standards while enabling teams with clear, pragmatic direction
• Foster a data‑aware and AI‑responsible culture through enablement and education rather than enforcement alone

What You Bring to the Team

• 6+ years of experience in data governance, data management, AI governance, security, or related operational leadership roles
• Experience governing unstructured or operational data (e.g., collaboration platforms, knowledge systems, document repositories)
• Strong understanding of data quality concepts and lifecycle management
• Familiarity with AI risk considerations including data provenance, bias, privacy, and misuse
• Demonstrated ability to drive cross‑functional execution without direct authority
• Excellent written and verbal communication skills for executive and technical audiences
• Sound judgment balancing governance rigor with business pragmatism
• High degree of ownership and follow‑through

What We’d Like to See (Not Required)

• Experience supporting AI governance, AI enablement, or responsible AI initiatives
• Exposure to regulated environments (HIPAA, HITRUST, SOC 2, GovRAMP, or similar)
• Familiarity with collaboration platforms such as Jira, Confluence, Slack, and Microsoft 365
• Experience partnering closely with Security, Legal, or Risk teams
• SaaS or data‑platform operating environment experience

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role

As a Product Owner in the AI Solutions team, you will play a pivotal role in translating strategic direction into actionable product increments. You will work closely with engineering teams in India, Nepal, and the US to ensure that our generative AI platform delivers measurable value to healthcare payers, with a focus on key business cases (i.e. Payment Integrity) and unstructured data solutions. This is an execution-focused role, responsible for the “how” of delivery and sprint cadence, while closely partnering with the Senior Product Manager who drives the “what” and “why.”

Your day to day

• Create and maintain a structured product backlog for GenAI solutions, ensuring clear problem statements, acceptance criteria, and definitions of done.
• Own GenAI stories in Jira, maintaining distinct boards, sprint cadences, and capacity visibility as defined by team processes.
• Break down high-level product and governance objectives into actionable user stories and tasks.
• Lead grooming sessions with engineers, data modeling, stakeholders, and others to clarify scope, estimate effort, and prioritize work based on business value and readiness.
• Drive sprint planning, coordinate daily stand-ups for the AI team, and proactively remove blockers to ensure commitments are met and deliverables align with the roadmap.
• Define and execute acceptance testing for completed features, verifying that data traceability, outputs, and governance capabilities meet requirements.
• Coordinate with security and compliance to ensure features meet auditability, observability, and hallucination control guardrails.
• Prepare release notes, user guides, and internal training materials; support deployments with DevOps and ensure client-facing documentation reflects new capabilities.
• Act as a liaison between product leadership, engineering, data modeling, and platform teams; communicate progress and issues clearly.
• Track and report on key SDLC metrics (burndown, velocity, throughput, capacity) and maintain a knowledge base of FAQs, lessons learned, and key decisions.
• Champion continuous improvement by applying agile best practices, identifying process bottlenecks, and leveraging AI tools for backlog management and documentation.

What you bring to the team

• 3+ years as a Product Owner or similar role in a data-driven environment, ideally supporting AI, data platforms, or healthcare products.
• Experience working with distributed engineering teams, preferably across US and India time zones, and familiarity with Scrum/Agile methodologies and tools (e.g., Jira, Confluence).
• Demonstrated ability to translate strategic product direction into actionable backlog items, groom stories with engineers, and manage sprint cadence.
• Strong understanding of the software development lifecycle (SDLC) and release management, with the ability to coordinate acceptance testing and quality assurance.
• Exposure to healthcare data (claims, clinical, or payer workflows) and AI/ML technologies.
• Excellent communication and organizational skills; comfortable interfacing with technical and non-technical stakeholders across product, engineering, security, and sales.
• Fluency in English (required for India-based roles).

What we would like to see, but not required

• Experience with healthcare interoperability standards (e.g., HL7 V2, FHIR, X12).
• Experience with cloud technologies (AWS, Azure, GCP), Databricks, or Snowflake.
• Prior work in a high-growth, fast-paced startup environment.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role

We are seeking a Senior Data QA Engineer to own and elevate data quality across our data platforms and client solutions. In this role, you will lead complex data validation efforts, shape testing strategies, and act as a trusted partner to Engineering, Product, and Operations. You’ll set standards for data quality, drive automation, and help ensure the delivery of reliable, production‑grade data solutions at scale.

Your Day to Day

• Lead data quality strategy and execution across multiple projects and datasets.
• Partner closely with Engineering, Product, Operations, and Project Management to influence data design and quality outcomes early in the lifecycle.
• Perform advanced data analysis and validation on large‑scale, client‑specific and healthcare datasets.
• Design, execute, and review complex test plans and test cases, including automated and manual testing approaches.
• Identify systemic data quality risks, drive root‑cause analysis, and partner with teams through resolution.
• Define, refine, and document QA standards, best practices, and verification protocols.
• Mentor junior QA engineers and provide guidance on testing methodologies and data validation techniques.
• Contribute to continuous improvement of QA processes, tooling, and workflows.

What You Bring to the Team

• Bachelor’s degree in Computer Science, Health Science, or a related field (or equivalent practical experience).
• 5+ years of experience in data quality, data QA, or testing roles within data‑driven environments; healthcare experience strongly preferred.
• Advanced SQL skills with the ability to validate, troubleshoot, and reason about complex datasets.
• Strong understanding of data pipelines, integrations, and large‑scale data systems.
• Experience working with healthcare data domains such as enrollment, claims, and provider data.
• Demonstrated ability to lead QA efforts, influence cross‑functional teams, and operate with a high degree of ownership.
• Excellent analytical, problem‑solving, and prioritization skills in fast‑moving environments.
• Strong communication skills, with the ability to explain data quality issues and risks to both technical and non‑technical stakeholders.
• Deep understanding of QA methodologies, testing frameworks, and best practices.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role

We are seeking an experienced Business Solution Manager to support client engagements by translating business needs into effective, data‑driven solutions. This role partners closely with clients and internal teams to define requirements, validate solutions, and ensure successful delivery across a range of business domains and data use cases.

Your day to day

Client Solutions & Requirements Management

• Lead client requirements gathering and analysis in partnership with subject matter experts
• Develop clear, structured Business Requirements Documents (BRDs) including acceptance criteria and non‑functional requirements
• Translate client needs into solution deliverables such as reports, dashboards, data extracts, and analytical views

 Solution Validation & UAT

• Validate delivered solutions against documented requirements and acceptance criteria
• Support and coordinate User Acceptance Testing (UAT) with client teams, working in alignment with internal QA resources

 Cross‑Functional Collaboration

• Partner with Product, Engineering, Account Management, Program Management, and Sales teams to deliver client solutions
• Contribute client insights to product roadmap discussions and solution improvements

 Client Relationship & Enablement

• Act as a trusted client partner throughout implementation and ongoing engagement
• Support client onboarding, training, and enablement activities
• Assist internal teams in understanding client use cases and solution intent

 Product & Process Improvement

• Maintain strong awareness of product capabilities, enhancements, and releases
• Identify opportunities to improve processes, solution quality, and client satisfaction

What you bring to the team

• Bachelor’s degree in Business, Computer Science, Information Systems, or equivalent relevant professional experience
• 5+ years of experience in business analysis, solution management, or client‑facing roles in software or data‑driven environments
• Proven experience gathering, documenting, and validating business requirements
• Ability to communicate effectively with both technical and non‑technical audiences
• Strong organizational skills with the ability to manage multiple priorities
• Analytical, detail‑oriented problem solver with a collaborative mindset
• Self‑motivated, adaptable, and comfortable working in a fast‑paced environment

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role:

As a Product Owner at Abacus Insights, you will play a pivotal role in bringing to market a cutting-edge cloud data platform which enables an industry leading data usability for healthcare payers, ultimately enabling them to turn their vast data into insights that drive improved outcomes. This role requires a robust background in software development or data engineering to effectively translate high-level product vision and customer needs into detailed requirements. You will be working collaboratively with engineering and stakeholders from across the organization to ensure the development of features that optimize value and meet customer needs. As a key member of the product team, you will be responsible for managing Abacus products throughout their lifecycle to include opportunity identification, demand intake, roadmap management, requirement development and analysis, story grooming, design reviews, product acceptance, go-to-market, and sunset planning. This role requires a person who can successfully manage across all aspects of product management while keeping focused on delivering true customer ROI and excelling as a technical translator of business need into technical specifications.

Your day to day: 

• Translate the strategic direction set by the Product Manager into specific product features and oversee development of these features efficiently within the agile framework.
• Support engineers comprehensively throughout all aspects of the Software Development Life Cycle (SDLC), providing guidance, insights, and assistance as necessary.
• Assume end-to-end responsibility for the lifecycle of product features you own
• Act as the primary translator between business needs and technical requirements, effectively bridging the gap to ensure alignment between stakeholders and engineering teams.
• Work with cross-functional teams to analyze current product performance and identify areas for improvement.
• Communicate comprehensive updates, progress reports, and insights related to the product's development to company leadership and other audiences.
• Collaborate with stakeholders, customers, and the development team to gather comprehensive requirements and document customer scenarios, pain points, and success criteria for product feature-sets and features.
• Estimate anticipated impact of each product feature and craft effective value statements to be used in roadmap prioritization.
• Create, prioritize, and manage the product backlog to ensure that the team is working on the most valuable items first.
• Ensure that the development team understands the scope and complexity of the tasks and can accurately estimate the level of development effort.
• Participate in sprint planning, reviews, and retrospectives, ensuring that the development team is building the product as envisioned and meeting the acceptance criteria.
• Act as the primary liaison between stakeholders and the development team, conveying updates, managing expectations, and gathering feedback.
• Ensure visibility, transparency, and clarity of the product backlog for all stakeholders involved.
• Manage product acceptance testing phases to ensure features not only add value but also align with customer needs.
• Coordinate release activities to ensure seamless deployment.
• Prepare relevant documentation and conduct internal user training for new features.
• Collaborate with client management to ennsure they have what they need to support our clients in optimizing the impact of the product.

What you bring to the team:

• 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.

What we would like to see, but not required:

• 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.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role:
As a Senior AI Engineer, you will help architect, build and implement our AI platforms, working closely with data quality engineers, data/software engineers, platform engineers, DevOps, product owners and business.  You provide technical leadership for multiple, diverse, and geographically distributed teams. You will coach and guide teams to enable future success. Also be a partner with engineering managers, directors and VP on strategic initiatives and future business growth opportunities especially around AI and ensuring the engineering organization can scale to meet the need.

As a member of the engineering team, you are responsible for coaching, mentoring, and driving change to enable us to better deliver and innovate in an agile environment.

Your day to day:

• Help shape the direction of our applied AI areas and intelligence features in our products. Drive the deployment of state-of-the-art AI models and systems that directly impacts on the capabilities and performance of Abacus’s products and services (e.g., Abacus Agents, MCP, SQL and RAG agents and tools, etc.)
• Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains
• Design and implement ML/AI pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation, iteration and self-healing
• Work closely with cross-functional teams, including AI engineers, data engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction
• Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model and GenAI system performance
• Skillful at driving critical projects (e.g. AI and data engineering Innovation, Development Productivity and Benchmarking)
• Meaningful experience in the world of Data and AI
• Capable of credible customer interactions
• Mentoring development team members to ensure delivered solutions adhere to the software architecture strategy, coding standards, and established organizational policies and procedures
• Participating in software architectural discussions, influencing decisions, and collaborating with peers to maintain consistency across the organization
• Identifying people and process improvement strategies for the Agile/Scrum team(s), especially for AI projects/teams where innovation and iteration are critical
• Communicate organizational updates to ensure teams adhere to the established policies and procedures
• Ensure projects are completed on time and according to our quality standards
• Facilitates communication upward around architecture, design, and implementation objectives
• Proven experience in leading software development teams or projects
• Excellent knowledge of software development design, QA and test automation, and experience with agile development methodologies
• Demonstrated knowledge of Cloud Architecture, AI Architecture, Agents/Agentic systems, Massive Parallel Processing (MPP) compute frameworks for Data+AI platforms, Security, and MCP/API based services
• Good understanding of Incident Management, Configuration Management, Operational efficiency and Customer Escalation Management preferred. Can manage the balance of deliveries on our roadmap commitments while dealing with interruptions and client escalations
• Good experience with open source
• 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.

What you bring to the team:

• 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

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST