Senior AI Engineer

Ciklum; Chennai District; On-site; INR 2,400,000 - 4,800,000; Full time

Job summary

Ciklum is seeking a Senior AI Engineer to join a cross-functional team developing tomorrow's AI-enabled experiences. You will embed with client teams, map complex workflows, and engineer autonomous AI-agent solutions to replace manual processes.

You will own the solution lifecycle end-to-end: discovery, architecture, build, deployment, and iteration, serving as the technical authority bridging agentic architectures with business outcomes.

Qualifications

• Hands-on with Strands as a primary framework; familiar with LangGraph, CrewAI or AutoGen.
• Deep knowledge of tool use, function calling, streaming, context management and prompts.
• Experience building/consuming MCP servers and multi-agent coordination (A2A) and task delegation.
• RAG pipelines: vector databases (Pinecone, pgvector, OpenSearch), embeddings and retrieval.
• Design reusable agent skills with observability, guardrails and human-in-the-loop checks.

Responsibilities

• Client Embedding & Workflow Discovery: Partner with business stakeholders to map manual processes into agentic workflows.
• Agentic AI Engineering: Design, build, and deploy multi-agent systems and function calling pipelines.
• End-to-End System Ownership: Develop production-ready backend services and integration layers for AI agents.
• Cloud & Infrastructure Management: Package, host, and scale agent workloads using modern cloud architectures with CI/CD.
• Safety & Observability: Implement guardrails and human-in-the-loop checkpoints to ensure reliability.

Skills

Python

Async programming

REST APIs

Client-facing communication

Cloud concepts

Tools

Strands

LangGraph

CrewAI

AutoGen

FastAPI

Docker

GitHub Actions

AWS AgentCore

Job description

Job Summary

As a Senior AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow, who thrives at the intersection of cutting-edge AI technology and real-world business execution. In this role, you wont just write code in a silo you will embed directly with client teams, map complex and manual workflows, and engineer autonomous AI-agent solutions to replace them.

You will own the solution lifecycle end-to-end: discovery, architecture, build, deployment, and iteration. Working with minimal direction, you ll serve as the technical authority who bridge the gap between complex agentic architectures and high-impact business outcomes.

Responsibilities

• Client Embedding & Workflow Discovery: Partner directly with business stakeholders to break down manual enterprise processes, map complex decision-making steps, and translate them into robust agentic workflows
• Agentic AI Engineering: Design, build, and deploy custom multi-agent systems, function-calling pipelines, RAG implementations, and reusable agent skills
• End-to-End System Ownership: Develop production-ready backend services and integration layers to connect AI agents with core enterprise platforms (e. g. , SharePoint, Jira, SAP, email)
• Cloud & Infrastructure Management: Package, host, and scale agent workloads using modern cloud architectures (AWS AgentCore, serverless, containerized environments) with automated CI/CD
• Safety & Observability: Implement guardrails, human-in-the-loop checkpoints, and agent evaluation loops to ensure reliability, mitigate hallucinations, and ensure enterprise compliance

Requirements

• Agentic AI & LLMs
  • Frameworks: Hands-on experience with Strands (primary framework), along with familiarity in LangGraph, CrewAI, or AutoGen
  • Agent Core Concepts: Deep understanding of tool use, function calling, streaming, context management, system prompts, and chain-of-thought methodologies
  • MCP & Agent Protocols: Proven ability to build/consume Model Context Protocol (MCP) servers, alongside multi-agent coordination (A2A), task delegation, and result aggregation
  • RAG Pipelines: Hands-on build experience with vector databases (e.g. , Pinecone, pgvector, OpenSearch), chunking strategies, embeddings, and retrieval optimization
  • Skill Building & Guardrails: Design reusable skills for agent consumption; implement observability, hallucination mitigation, and human-in-the-loop checkpoints
• Backend Development & Data
  • Python Mastery: Strong experience with Python 3.10+ using async/await and strict type hinting
  • APIs & Web Frameworks: Proficiency with FastAPI (or equivalent), REST API design, and modern auth flows (JWT / OAuth2)
  • Data Processing: Solid SQL skills (queries, filters, joins) and expertise in unstructured data processing (extracting/classifying data from PDFs, Excel, and legacy enterprise documents)
• Infrastructure & DevOps
  • AWS & Hosting: Experience hosting/operating agent workloads using AWS AgentCore (understanding lifecycle, scaling, and invocation patterns) along with core services (EC2/ECS, Lambda, RDS, S3)
  • Containers & CI/CD: Docker proficiency and experience setting up GitHub Actions pipelines
• Qualifications & Experience
  • Software Engineering Track Record: Strong foundation in core software engineering principles and production-grade software development
  • Production LLM Experience: At least one production project successfully delivered using LLM agents, skill-building architectures, or RAG pipelines
  • End-to-End Ownership: Demonstrated ability to drive projects independently from zero to one with minimal guidance
  • Client-Facing Communication: Comfortable interfacing with non-technical business partners gathering requirements, explaining technical decisions, and presenting live solutions