AI Automation Engineer (Python & LLM)

Accelon Inc.; Bengaluru; Hybrid; INR 4,500,000 - 7,000,000; Full time

Benefits offered by this job

Healthcare coverage

Work-life balance

Healthy work culture

Provident fund & gratuity

Job summary

Accelon Consulting seeks a seasoned AI Automation Engineer to design and run AI-powered workflows. You will deploy end-to-end automations that integrate LLMs with internal systems, APIs, and data sources, and build RAG pipelines for reliable grounded responses.

You will implement MCP servers, vector stores, and robust CI/CD while collaborating with stakeholders to scope requirements and delivery milestones.

Qualifications

• 3-5 years of professional software, data, or automation engineering experience, including at least 1 year building with LLMs or AI services.
• Strong Python skills including async programming, API integration, testing, and clean code.
• Practical experience with LLM APIs (Anthropic Claude, OpenAI, Gemini, Bedrock) in real applications.
• Hands-on experience with at least one agent or orchestration framework (LangChain, LangGraph, Llamalndex, CrewAI, Semantic Kernel, AutoGen, or equivalent).
• Experience building RAG systems and working with vector stores (pgvector, Pinecone, Weaviate, Qdrant, Milvus, OpenSearch, or similar).
• Solid grasp of prompt engineering, context design, and structured output techniques.
• Familiarity with Model Context Protocol (MCP) and building MCP servers.
• Strong REST/GraphQL API integration skills including OAuth, token-based authentication, webhooks, pagination, and rate-limit handling.
• Working knowledge of SQL and data modeling.
• Experience with Git workflows, code review, and CI/CD.
• Cloud experience on AWS, Azure, or GCP including compute, serverless functions, queues, secrets management, and managed AI services.
• Containerization fundamentals with Docker.
• Proven ability to work directly with stakeholders for requirements elicitation, demos, and expectation management.

Responsibilities

• Design, build, and operate AI-powered automations to eliminate manual effort in business and engineering workflows.
• Build and deploy end-to-end AI automations and agentic workflows integrating LLMs with internal systems, APIs, and data sources.
• Design and implement retrieval-augmented generation (RAG) pipelines including chunking, embedding, vector search, re-ranking, and grounded response generation.
• Develop tool- and function-calling integrations for agents to act on systems of record.
• Partner with business stakeholders to map processes, quantify manual effort, and prioritize automation backlog.
• Write production Python services and jobs with logging, retries, and error handling.
• Build prompt and model evaluation harnesses including golden datasets, regression tests, and quality gates.
• Instrument automations with observability and tracing for early detection of failures and quality drift.
• Implement human-in-the-loop checkpoints and approval steps where full autonomy is inappropriate.
• Optimize for cost and latency through model selection, caching, batching, and prompt compression.
• Document architecture, runbooks, and handover material; support and iterate on automations post-launch.
• Follow security, privacy, and responsible AI requirements around data handling and model usage.

Skills

Python

Async programming

LLM APIs

Agent frameworks

RAG systems

Prompt engineering

MCP servers

REST/GraphQL

SQL

Git workflows

CI/CD

AWS/Azure/GCP

Docker

Education

Bachelor's degree in CS/Engineering or related

Tools

LangChain

LangGraph

LlamaIndex

CrewAI

Semantic Kernel

AutoGen

pgvector

Pinecone

Weaviate

Qdrant

Milvus

OpenSearch

Job description

Job Description

• Design, build, and operate AI-powered automations to eliminate manual effort in business and engineering workflows.
• Build and deploy end-to-end AI automations and agentic workflows integrating LLMs with internal systems, APIs, and data sources.
• Design and implement retrieval-augmented generation (RAG) pipelines including chunking, embedding, vector search, re-ranking, and grounded response generation.
• Develop tool- and function-calling integrations for agents to act on systems of record.
• Partner with business stakeholders to map processes, quantify manual effort, and prioritize automation backlog.
• Write production Python services and jobs with logging, retries, and error handling.
• Build prompt and model evaluation harnesses including golden datasets, regression tests, and quality gates.
• Instrument automations with observability and tracing for early detection of failures and quality drift.
• Implement human-in-the-loop checkpoints and approval steps where full autonomy is inappropriate.
• Optimize for cost and latency through model selection, caching, batching, and prompt compression.
• Document architecture, runbooks, and handover material; support and iterate on automations post-launch.
• Follow security, privacy, and responsible AI requirements around data handling and model usage.

Requirements

Must-Have:

• 3-5 years of professional software, data, or automation engineering experience, including at least 1 year building with LLMs or AI services.
• Strong Python skills including async programming, API integration, testing, and clean code.
• Practical experience with LLM APIs (Anthropic Claude, OpenAI, Gemini, Bedrock) in real applications.
• Hands-on experience with at least one agent or orchestration framework (LangChain, LangGraph, Llamalndex, CrewAI, Semantic Kernel, AutoGen, or equivalent).
• Experience building RAG systems and working with vector stores (pgvector, Pinecone, Weaviate, Qdrant, Milvus, OpenSearch, or similar).
• Solid grasp of prompt engineering, context design, and structured output techniques.
• Familiarity with Model Context Protocol (MCP) and building MCP servers.
• Strong REST/GraphQL API integration skills including OAuth, token-based authentication, webhooks, pagination, and rate-limit handling.
• Working knowledge of SQL and data modeling.
• Experience with Git workflows, code review, and CI/CD.
• Cloud experience on AWS, Azure, or GCP including compute, serverless functions, queues, secrets management, and managed AI services.
• Containerization fundamentals with Docker.
• Proven ability to work directly with stakeholders for requirements elicitation, demos, and expectation management.

Nice-to-Have:

• Experience with workflow automation platforms (n8n, Zapier, Power Automate, Airflow, Temporal, Prefect, Dagster).
• Background in RPA (UiPath, Automation Anywhere, Blue Prism) and modernizing RPA automations with AI.
• Experience with LLM observability and evaluation tooling (LangSmith, LangFuse, Arize, Braintrust, Ragas, DeepEval).
• Multi-agent system design including planner/executor patterns and supervisor architectures.
• Document intelligence and multimodal work (OCR, PDF parsing, table extraction, vision models).
• Frontend familiarity (React.js, Next.js, TypeScript) for internal tools and demos.
• Infrastructure-as-code (Terraform, CloudFormation) and Kubernetes exposure.
• Experience with enterprise governance concerns including AI risk review, audit trails, data residency, and access-scoped retrieval.
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience.

Why Join Us

Accelon Consulting is a global workforce solutions partner and AI enablement leader, but above all, we are a people-first organization. Our dual commitment is simple: advancing careers and enabling organizations to thrive in a connected, intelligent future. Our culture is built on respect, transparency, and long-term growth, offering opportunities to work on high-impact projects with leading global enterprises. At Accelon, people are supported, achievements are recognized, and careers are built with purpose. To learn more about our culture and what it’s like to be part of our team, visit the Life at Accelon section on our website.

We Offer:

• Healthcare Coverage – available for you and your immediate family.
• Work-Life Balance – flexible work arrangements and realistic workloads to support employee well-being.
• Healthy Work Culture – a collaborative, respectful, and growth-oriented work environment.
• Provident Fund & Gratuity – benefits provided in accordance with applicable statutory requirements.