Role: Engineer
Required Skills: Artificial Intelligence | Machine Learning
Qualification: BACHELOR OF ENGINEERING
Experience: 6 - 8 Years
Function: TECHNOLOGY
Apply By: 2027-01-03
Must Have Technical/Functional Skills
- Bachelor's degree in Computer Science, Engineering, Data Science, a related field, or equivalent relevant
professional experience.
- 10+ years of hands-on software engineering experience in deploying distributed systems and cloud-native
solutions.
- 9+ years of experience operating in a consulting or advisory capacity, including structuring ambiguous
problems, developing solution recommendations, and delivering against client or business objectives.
- 6+ years of hands-on AI/ML engineering experience, with strong exposure to Generative AI and modern
LLM-based application development.
- 2+ years of Forward Deployed Engineering (FDE), Applied AI Engineering, Customer Engineering, or
equivalent client-embedded engineering experience, working directly with customers to translate ambiguous
business needs into production solutions.
- Experience working with APIs, data pipelines, or distributed systems.
- Experience working with at least one cloud platform (e.g., AWS, Azure, or GCP).
- Demonstrated experience working in client-facing engagements, including partnering directly with stakeholders
to understand needs, communicate solutions, and support delivery in real-world environments.
- Experience building and deploying AI/ML solutions, including familiarity with LLMs, prompt engineering, and
model deployment patterns.
- Proficiency in modern development frameworks, APIs, and data integration approaches.
- Demonstrated advanced user capability on CodeX, Claude, etc. and other AI productivity tools.
- Proven ability to lead client engagements, including discovery, solution design, and delivery.
- Strong stakeholder management skills, with the ability to influence both technical and executive audiences.
- Experience structuring ambiguous problems and driving them to clear, actionable solutions.
- Excellent communication and storytelling skills, with the ability to adapt messaging to different audiences.
Programming & Scripting
- Languages: Python (primary for automation, APIs, and data pipelines).
- UI Skills using React JS (Primary) If not the Angular
API & Backend Engineering
- REST API development using Spring Boot, FastAPI, or Node.js.
- API integration using OAuth2/JWT authentication and API gateways such as Azure API Management or
Apigee.
- Data exchange formats: JSON and XML.
- HL7/FHIR experience is preferred.
AI/ML & GenAI Integration
- LLM integration using Azure OpenAI or OpenAI APIs.
Final approved job description
- Frameworks: LangChain and Semantic Kernel.
- Retrieval-Augmented Generation (RAG).
- Prompt engineering.
- Embeddings and vector databases, including Pinecone and Azure Cognitive Search.
Data Engineering & Handling
- Any SQL RDBMS.
- NoSQL - MongoDB preferred if not Cosmos DB. Vector Databases (Pinecone, FAISS, ChromaDB)
Additional Technical and Domain Requirements
- Mathematical & Actuarial Modeling: Practical understanding of actuarial methodologies, drug trend regression
forecasting, and predictive ML workflows applied to specialty pharmacy utilization.
- Security & Governance: Comprehe nsive understanding of HIPAA, HITRUST, and SOC 2 data security
standards governing Protected Health Information (PHI) and PII.
Industry & Domain Expertise (Non-Negotiable)
- Deep PBM Domain Fluency: 7+ years of rigorous experience within Pharmacy Benefit Management, Health
Plan Pharmacy Services, or Specialized PBM Technology/Auditing firms.
- Protocol & Standard Mastery: Expert familiarity with NCPDP standards (Telecommunication Standard D.0 and
above, SCRIPT, Post-Adjudication Standard), X12 EDI (834 enrollment, 837 claims, 835 remittance), and
modern HL7 FHIR US Core / Da Vinci implementations.
- Financial & Regulatory Mechanics: Comprehensive mastery of pharmacy pricing models (WAC, AWP, NADAC,
MAC), pass-through vs. spread pricing dynamics, manufacturer rebate contract administration, Medicare Part
D Star Ratings, coverage-gap mechanics, and CMS audit readiness.
Roles & Responsibilities
- Rapid Prototyping & Production Rollout: Embed with client cross-functional PBM teams to deliver
production-grade platforms, transitioning from discovery and proof-of-concept (PoC) to full enterprise
deployment in compressed cycles.
- Business-Value Attribution: Quantify and communicate the financial and operational impact of technical
solutions, linking platform architecture to measurable improvements in cost efficiency, reconciliation, audit
outcomes, and administrative processes.
Client Engagement & Leadership
- Partner directly with healthcare clients to understand strategic priorities, operational challenges, and digital
transformation goals.
- Lead discovery sessions, workshops, and solution design engagements with both technical and business
stakeholders.
- Act as a trusted advisor, guiding clients on how to apply AI/ML capabilities to real-world healthcare use cases,
such as claims, revenue cycle, clinical workflows, and member experience.
- Translate client needs into clear problem statements, solution architectures, and delivery roadmaps.
Solution Design & Architecture
- Design scalable, secure, and compliant AI-powered solutions aligned to healthcare industry requirements.
- Architect end-to-end systems integrating LLMs, machine learning models, APIs, and enterprise platforms.
Final approved job description
- Evaluate trade-offs between approaches, such as build vs. orchestrate, model selection, and latency vs.
accuracy, and communicate recommendations clearly to stakeholders.
- Ensure solutions are designed for real-world deployment, maintainability, and integration with existing client
ecosystems.
Solution Implementation & Delivery
- Build and deploy AI-powered solutions, including LLM-based workflows, copilots, and automation tools in client
environments.
- Implement integrations between AI models, APIs, and enterprise healthcare systems.
- Translate defined solution designs into high-quality, production-ready code.
- Contribute to end-to-end delivery by supporting development, testing, and deployment activities.
Software Engineering & Integration
- Develop scalable backend services and APIs using Python and FastAPI.
- Build RESTful APIs and enterprise integrations with business systems and third -party platforms.
- Create reusable components, automation workflows, and AI-enabled operational solutions.
- Implement human-in-the-loop (HITL) approval workflows and governance controls.
Hands-on Engineering
- Develop solution components using modern programming languages, such as Python, Java, and SQL, and
engineering frameworks.
- Rapidly prototype solutions to validate concepts, iterate with client feedback, and accelerate time-to-value.
- Build and deploy production-grade AI applications, including LLM-based workflows, copilots, and intelligent
automation solutions.
- Integrate AI agents and automation into client environments, optimizing for performance, scalability, and
reliability.
- Work with distributed systems and cloud platforms to support scalable, reliable deployments.
- Assist with data preparation, prompt configuration, and model integration for AI-driven solutions.
- Troubleshoot and resolve technical issues during development and deployment.
Client Delivery Support
- Work alongside senior engineers and consulting leads in client engagements across healthcare payer and
provider organizations.
- Support technical discussions and working sessions with client stakeholders.
- Help execute defined project plans, timelines, and deliverables.
- Contribute to iterative development cycles, incorporating client and team feedback.
Collaboration & Translation
- Partner with cross-functional teams, including engineering, platform, and product teams, to deliver integrated
solutions.
- Translate technical requirements into actionable development tasks.
- Communicate progress, risks, and technical considerations clearly within the team.
- Support alignment between technical implementation and client expectations.
Final approved job description
Documentation & Knowledge Transfer
- Document solution components, integration points, and deployment processes.
- Support knowledge transfer to client technical teams to enable adoption and sustainability.
- Contribute to reusable implementation patterns, assets, and playbooks.
Success Measures
- Delivers high-quality solution components that meet performance, reliability, and security expectations.
- Contributes effectively to end-to-end client delivery efforts.
- Demonstrates strong execution in translating requirements into working systems.
- Communicates clearly within teams and supports client delivery activities.
- Builds capability in both technical implementation and client engagement over time.
- Demonstrates the ability to design and develop prototypes with a clear path to production, ensuring solutions
are scalable, supportable, and can be transitioned effectively to production engineering teams
Salary Range: $180,000- $200,000 a year
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commut