Forward Deployment Engineer

• 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

• 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, BACHELOR OF ENGINEERING

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