Senior Artificial Intelligence/Machine Learning Engineer

Ciklum is looking for a Senior Artificial Intelligence/Machine Learning Engineer to join our team full-time in India. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.

About the role

As a Senior Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.

Responsibilities

Harness Engineering — Core Harness engineering — Excellent understanding of designing agent harnesses: the control loop, tool and skill surface, context and state management, and human-in-the-loop checkpoints around an LLM AWS Step Functions with ASL — Author Amazon States Language state machines to orchestrate agent steps, branching, retries, parallelism and human-approval gates (e.

g. task-token waits); invoke Agent. Core runtimes and Lambda from workflows Deterministic vs LLM control — Design workflows where policy gates and rules decide routing and the LLM only proposes, with explicit exception, timeout and loop-guard paths Amazon Bedrock Agent. Core — Host, operate and scale agent workloads on Agent.

Core Runtime; understand lifecycle, scaling and invocation patterns, and expose tools via Agent. Core Gateway Agent. Core Observability — Hands-on tracing, metrics and logging of agent runs (Agent. Core, Cloud. Watch, Datadog) with a per-step audit trail to debug and monitor production workflows Agent. Core Evaluation — Hands-on design and running of evaluations (Agent.

Core Evaluations, golden-dataset regression tests) to measure agent quality before and after each release Guardrails — Hands-on configuration of Amazon Bedrock Guardrails and policy controls for safety, prompt-injection defence, PII and hallucination mitigation, with human-in-the-loop review where required Agentic AI with Claude Claude Code / Cowork — Experience designing, deploying and scaling AI-powered production workflows using Claude Code and/or Cowork LLM API fundamentals — Tool use, function calling, streaming and context management Skill building — Design and publish reusable skills consumable by agent workflows MCP (Model Context Protocol) — Build, host and consume MCP servers (e.

g. FastMCP on Agent. Core); expose and integrate tools for agent use, with agents reaching data only through MCP/API, never directly Multi-agent coordination — Task delegation and result aggregation across agents (A2A) RAG pipelines — Vector databases, chunking, embeddings and retrieval Prompt engineering — System prompts, evaluation and iteration Front End AG-UI — Build agent-facing user interfaces on the AG-UI protocol, connecting the front end to running agents for streaming responses, tool-call visibility, shared state and human approval steps Back End Python 3.

10+ — async/await, type hints FastAPI or equivalent Python web framework Basic SQL — query, filter, join; awareness of vector DBs (pgvector, Pinecone, Open. Search) NoSQL — Working knowledge of document/key-value stores (e.g. Amazon DynamoDB): data modelling, access patterns, and using them for agent run state and audit trails REST API design, JWT / OAuth2 Workflow Automation Decompose manual business processes into agent workflows Document processing — PDF, Excel, unstructured data extraction and classification AI Engineer OCR — Extract text, tables and layout from scanned and image-based documents (e.

g. AWS Textract), and feed the output into agent workflows Enterprise system integration — SharePoint, email, and external systems via APIs and MCP Infrastructure AWS services — Lambda, ECS, RDS, S3, IAM — support agent deployment and data storage needs Terraform / Infrastructure as Code — Provision and promote Agent.

Core, Step Functions, Lambda and supporting AWS resources across environments Docker and containerisation GitHub Actions CI/CD Requirements: Proven experience in software engineering, with hands-on AI engineering shipped to production (years of experience are not the criterion; depth of AI delivery is) At least one production project involving LLM agents, skill building, or RAG pipelines — ideally on AWS Bedrock Agent.

Core and/or Step Functions Direct experience working with enterprise customers to design, deploy and scale AI-powered production workflows using Claude Code / Cowork Track record of owning and delivering solutions end-to-end with minimal guidance Experience working directly with non-technical stakeholders — gathering requirements, presenting solutions Consulting or client-facing background is an advantage Desirable: Kubernetes TypeScript Fine-tuning and model evaluation CRE domain knowledge What’s in it for you?

Strong community: Work alongside top professionals in a friendly, open-door environment Growth focus: Take on large-scale projects with a global impact and expand your expertise Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies Care: We’ve got you covered with company-paid medical insurance, mental health support, and financial & legal consultations About us: At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter.

With us, you’ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. India is a strategic innovation hub for Ciklum, with growing teams in Chennai and Pune leading advancements in Edge. Tech, AR/VR, IoT, and beyond. Join us to collaborate on game-changing solutions and take your career to the next level.

Explore, empower, engineer with Ciklum! Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum. #LI-RB1