Experience Level: 3 - 15 years
Location: Hyderabad / Pune
Qualification: BTech/MTech/MCA
Mode of Work: Hybrid
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.
Skills Required
- BTech, MTech, or MCA degree
- 3-15 years of professional experience
- Strong production-grade Python experience, including clean code, testing, APIs, and enterprise integrations
- Hands-on experience building multi-agent systems using Amazon Bedrock and Bedrock AgentCore
- Experience with prompt engineering and tool calling
- Experience with agent orchestration frameworks such as Strands Agents, LangGraph, or LangChain
- Experience building retrieval pipelines using embeddings, chunking, and vector search
- Working knowledge of AWS Lambda, ECS or EKS, API Gateway, S3, DynamoDB, and IAM
- Production engineering experience with CI/CD, automated testing, monitoring, AI evaluations, and guardrails
What We Do
DATAECONOMY is a global, cloud-first data and AI consultancy delivering enterprise-grade solutions through an innovative intellectual-property suite. Its work spans data and BI platform modernization, self-service AI, data mesh and fabric, master data management, governance, cloud enablement, digital engineering, knowledge graphs, and machine lakes supporting cybersecurity and financial-crime use cases for enterprise clients.
