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TC
Tata Consultancy Services Limited
Senior Forward Deployed Engineer
Career Insights for Platform Engineer
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Based on Maryland data
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What they do
A Platform Engineer is responsible for the development of platforms that support the needs and use cases of different engineering teams across the organization. Creates reusable tools and workflows to streamline operational needs and facilitate automation tasks, supporting scalability of DevOps practices.
$129,369 / year median in Maryland
Job Description
Must Have Technical/Functional Skills
- 12+ years of software/data engineering experience with strong hands-on delivery of AI, GenAI, LLM, RAG and agentic AI solutions in enterprise environments.
- Proven experience leading prototype-to-production delivery of Claude based AI solutions, preferably using Anthropic Claude on Amazon Bedrock.
- Strong Python engineering skills with production API development experience using FastAPI, Flask or similar frameworks.
- Hands-on experience with agentic orchestration patterns and frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen or similar.
- Deep experience with RAG pipelines, embeddings, vector databases, semantic search, document ingestion, re-ranking, grounding and LLM evaluation.
- Strong AWS implementation experience across Bedrock, Lambda, API Gateway, Step Functions, ECS/EKS, S3, IAM, KMS, CloudWatch, CloudTrail and CI/CD.
- Experience integrating AI solutions with enterprise APIs, data platforms, workflow platforms, knowledge repositories and in-house capabilities.
- Strong understanding of tool/function calling, MCP servers, guardrails, validation, human-in-the-loop patterns, observability, latency and cost optimization.
- Functional exposure to Asset Management, Investment Operations, Distribution, Client Reporting or Middle Office processes is preferred. Roles & Responsibilities
- Lead hands-on build, deployment and productionization of Claude based agentic AI, RAG and LLM solutions on AWS and enterprise internal platforms.
- Partner directly with business users, domain SMEs, architects, security, cloud and data teams to convert ambiguous needs into working AI products.
- Own solution design for agent workflows, API/tool integrations, prompt templates, evaluators, guardrails, human approval flows and exception handling.
- Drive rapid discovery, prototyping, MVP delivery, production hardening and scale-up across prioritized asset management use cases.
- Provide technical leadership to FDEs and engineers through design reviews, code reviews, troubleshooting, reusable patterns and delivery governance.
- Integrate AI applications with internal systems, enterprise data sources, knowledge repositories, workflow tools and API ecosystems.
- Troubleshoot complex live issues including hallucination, retrieval quality, model behavior, latency, failed tool calls, orchestration errors and access constraints.
- Optimize performance, reliability and cost using caching, model routing, batching, prompt tuning, monitoring and architecture improvements.
- Ensure solutions align with enterprise security, IAM, encryption, audit logging, privacy, AI governance and model risk requirements.
- Create technical documentation, implementation plans, deployment runbooks, demos and transition materials for support and long-term adoption. Generic Managerial Skills, If any
- Strong client-facing leadership with ability to communicate complex AI solutions clearly to business, domain, architecture and engineering stakeholders.
- Ability to lead in ambiguous environments, structure problem statements and drive fast iterative delivery with measurable outcomes.
- Strong collaboration skills across product owners, SMEs, security, cloud, data, architecture and delivery teams.
- Ownership mindset with ability to independently drive PoCs, MVPs, production fixes, technical decisions and delivery commitments.
- Strong prioritization, risk management, issue escalation and stakeholder alignment skills in live enterprise environments.
- Ability to mentor engineers, establish reusable engineering patterns, enforce code quality and promote disciplined delivery practices.