Automation and AI Developer

Thomson Reuters

. Design, build, and own intelligent automation and AI solutions from concept to production .

Posted 10/9/2026full-timeBengaluru • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing intelligent automation and AI solutions, with a strong focus on LangGraph and AWS technologies. Proficient in building production-grade Python applications and evaluating low-code versus pro-code solutions.

Highest-signal resume keywords

LangGraph ExperienceAWS AgentCore ProficiencyProduction-Grade Python DevelopmentEnd-to-End RAG Pipeline ExperienceGenAI/LLM Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LangGraphPythonFastAPIPydanticAWSSQLRAG PipelineEmbeddingsChunkingLow-Code Automation

Soft Skills

MentoringCollaborationProblem-Solving

Tools & Technologies

Microsoft Copilot StudioPower AutomatePineconeChromaDBOpenSearchFAISSClaude CodeGitHub CopilotCursorCline

Certifications & Qualifications

AWS AI/ML CertificationGCP AI/ML CertificationAzure AI/ML Certification

Industry Keywords

Document IntelligenceOCREnterprise IntegrationSAP HANASalesforce Connectors

Tech Stack

Tools & technologies

AWSAzureGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Design, build, and own intelligent automation and AI solutions from concept to production
Implement LangGraph agentic workflows on AWS AgentCore, including state graphs, tool orchestration, conditional routing, and error recovery
Build custom RAG pipelines end-to-end, including chunking strategy, embeddings, vector retrieval, and accuracy evaluation
Contribute to rapid proof-of-concept delivery with the Architect and Lead
Write production-grade Python using FastAPI and Pydantic, with testing and proper error handling
Use AI coding tools to accelerate builds and own and fix generated code in production
Build low-code automations using Microsoft Copilot Studio and Power Automate when appropriate
Evaluate Pro Code versus Low Code trade-offs and identify when Low Code is the better fit
Stay current with evolving Low Code platform capabilities
Own production components by monitoring, debugging, optimizing, and iterating
Independently debug agent failures involving context issues, tool errors, hallucinations, and retrieval degradation
Collaborate with the Lead on architecture translation and implementation planning
Mentor Associate Developers through code reviews and pair programming

Requirements

What you’ll need

3–5 years of total experience
1–2 years of GenAI/LLM experience
6–12 months of LangGraph experience
2–3 projects with working code
Hands-on LangGraph experience with state graphs, conditional routing, and checkpointing; primary, non-negotiable framework
Solid foundational knowledge of LangChain, including chains, memory, and custom tools
Hands-on AWS AgentCore preferred; strong LangGraph depth with ramp path acceptable
AWS Bedrock experience with model invocation, knowledge bases, and guardrails
SQL proficiency, NL-to-SQL, and LLM-powered query and insight patterns; Snowflake is a plus
End-to-end RAG pipeline experience, including chunking, embeddings, retrieval, and evaluation
Hands-on experience with at least one of Pinecone, ChromaDB, OpenSearch, or FAISS
Production-quality Python, including type hints, async/await, FastAPI, and Pydantic
Understanding of trade-offs across OpenAI, Claude, Gemini, and Llama
Ability to build with Microsoft Copilot Studio and Power Automate when use cases fit
Experience with Claude Code, GitHub Copilot, Cursor, or Cline; ability to own and fix generated code
Hands-on AWS AgentCore Runtime, Memory, and Tools Gateway
MCP/A2A server or client implementation, or protocol awareness
Enterprise integration experience with SAP HANA and Salesforce connectors
Document intelligence experience, including OCR and layout-aware chunking
Experience with RAGAS, Promptfoo, or DeepEval
AWS, GCP, or Azure AI/ML certifications
Availability for 1pm IST to 10pm IST shift
Ability to work hybrid, 3 days from the office

Benefits

Comp & perks

Hybrid working environment with 2–3 days a week in the office depending on the role
Work from anywhere for up to 8 weeks per year
Flexible vacation
Two company-wide Mental Health Days off
Access to the Headspace app
Retirement savings
Tuition reimbursement
Employee incentive programs
Resources for mental, physical, and financial wellbeing
Two paid volunteer days off annually
Opportunities to participate in pro-bono consulting projects and ESG initiatives
Flexible work arrangements
Career development, continuous learning, and skills development through Grow My Way programming
Supportive workplace policies through Flex My Way
Reasonable accommodations for qualified individuals with disabilities and sincerely held religious beliefs