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DATAECONOMY

FDE - Agentic Ai

Hyderabad / Pune, INOn-sitePermanentFull-time

Posted Sep 26, 2026

Job Title: FDE - Agentic Ai
Experience Level: 3 - 15 years
Location: Hyderabad / Pune

Qualification: BTech/MTech/MCA
Mode of Work: Hybrid



We are seeking a Forward Deployed Engineer (FDE) works directly inside a strategic enterprise customer to design, build, deploy and run AI-powered production systems alongside the customer's engineering team. FDEs write production-grade software and own outcomes end to end, from prototype through enterprise-scale deployment.
The role combines the technical rigor of a software engineer with the urgency and ownership needed to deliver measurable business outcomes. FDEs also create reusable architectures, patterns and engineering practices that help the wider FDE practice scale.


Key Responsibilities:

•     Embed with customer engineering teams: Understand the customer's business processes, technical architecture and operational constraints. Turn ambiguous business problems into scalable, AI-enabled production systems.

•     Build production AI applications: Design and develop production-grade software for AI and agentic workflows, including multi-agent orchestration, retrieval pipelines, workflow automation and decision intelligence. Integrate foundation models, customer data sources, APIs and existing applications into cohesive AI experiences. Optimize for latency, reliability, observability, cost and security.

•     Own production: Take systems from design through production rollout and ongoing operations. Troubleshoot incidents across AI models, distributed systems, data pipelines and application services. Put in place monitoring, evaluations, guardrails, testing, CI/CD, rollback and resiliency mechanisms that keep AI systems healthy at scale.

•     Accelerate customer transformation: Identify opportunities to expand AI adoption across customer workflows. Build reusable patterns, accelerators and reference architectures for future engagements.

•     Raise the bar: Mentor engineers and contribute to engineering best practices for AI and forward deployment. Feed reusable components and learnings back into products and services.



Requirements


  • Python: Strong, production-grade Python — clean code, testing, APIs, and integration with enterprise systems.
  • Agentic AI on AWS: Hands-on experience building multi-agent systems on Amazon Bedrock and Bedrock AgentCore, including:
    • Prompt engineering
    • Tool calling
    • Agent orchestration with a framework (e.g., Strands Agents, LangGraph, LangChain)
  • RAG & Retrieval: Building retrieval pipelines, including:
    • Embeddings
    • Chunking
    • Vector search (e.g., Bedrock Knowledge Bases, OpenSearch, pgvector)
  • Core AWS Services: Working knowledge of:
    • Serverless and container services (e.g., Lambda, ECS/EKS)
    • API Gateway
    • Storage (e.g., S3, DynamoDB)
    • Security and networking (e.g., IAM)
  • Production Engineering: Experience taking AI systems to production, including:
    • CI/CD
    • Automated testing
    • Monitoring
    • Evaluations and guardrails for AI output



Benefits

  • Comprehensive Medical Coverage:
    Health insurance of INR 7.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind.
  • Robust Protection Plans:
    Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones.
  • Retirement Benefits:
    PF and Gratuity provided as per standard government regulations.
  • Flexible Work Options:
    Enjoy hybrid work arrangements & flexible working hours
  • Generous Leave Policy:
    21 days of annual leave, in addition to 10 company-declared holidays.
  • Employee Well-being Spaces:
    Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.


Role snapshot

Job type

Full-time

Required skills

Production-grade Python (clean code, testing, APIs, enterprise integration)Agentic AI on AWS (building multi-agent systems on Amazon Bedrock and Bedrock AgentCore)Prompt engineering for agentic workflowsTool calling and integration within agent workflowsAgent orchestration frameworks (e.g., LangChain, LangGraph, Strands Agents)RAG & retrieval pipelines (embeddings, chunking, vector search)Vector search technologies (Bedrock Knowledge Bases, OpenSearch, pgvector)Core AWS services for deployment (Lambda, ECS/EKS, API Gateway, S3, DynamoDB, IAM)Production engineering for AI systems (CI/CD, automated testing, monitoring, rollback, resiliency)Monitoring, observability and incident troubleshooting for distributed AI systems and data pipelinesSolution design / translating ambiguous business problems into scalable AI-enabled production systemsMentorship and driving engineering best practices for AI and forward deployment teams

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FDE - Agentic Ai at DATAECONOMY in Hyderabad / Pune | Scovai | Scovai