Lead Artificial Intelligence/Machine Learning Engineer

Job Description

Ciklum is looking for a

Lead 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 Lead Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team engineering experiences of tomorrow. Ciklum is seeking an AI Lead to head the AI engineering track of the project, an ambitious initiative to build an enterprise-grade Agent Development Platform (ADP). This role owns the technical decisions the entire program inherits: the agent framework architecture, the evaluation strategy that governs milestone acceptance, and the AI safety posture of a platform our client will commercialize to their own enterprise customers. You will lead a team of AI engineers through "Wave 1" establishing a production-ready foundation that decouples core infrastructure from individual agent business logic and set the patterns that make an agent-a-month delivery cadence achievable in year two. This is a hands-on leadership role: you are expected to architect, to review, and to write the hardest code yourself.

Responsibilities Technical Leadership & Architecture Ownership:

• Architecture Decision Records: Own the ADR process for the AI track , agent framework selection and ratification (LangGraph / Claude Agent SDK), orchestration topology, memory and state strategy, model routing policy. Defend these decisions to client architecture boards and revise them on evidence, not opinion
• Agent Reference Architecture: Define the canonical agent blueprint (planner/executor patterns, tool-use protocols, HITL gate placement, failure and compensation semantics) that all production agents , Lease Abstraction, CAM Reconciliation, and successors , are built from. Every deviation from the blueprint is a decision you approve
• Evaluation Strategy: Own the evaluation system as a first-class engineering discipline: ground-truth corpus design with client SMEs, field-level accuracy harnesses, LLM-as-judge calibration, and regression gates wired into CI. Milestone acceptance and commercial payments depend on these numbers, you are accountable for their integrity and defensibility
• AI Safety & Security Accountability: Own the platform's defense against prompt injection from untrusted document content, tool-call authorization boundaries, egress controls, and the adversarial test suite. Lead red-team exercises against recognized taxonomies (e.g., Microsoft AI Red Team) and sign off on the AI security posture per release
• Prodigy Stewardship: Own the technical integrity of the Prodigy accelerator within the engagement, what ships out-of-the-box versus what is customized, SBOM and licensing hygiene, and the upgrade path against the Prodigy roadmap. You are the engineer the client's CTO calls to verify our claims

Core AI Engineering & Delivery

• Hands-on Development: Personally build the highest-risk components , the agent SDK core, the evaluation harness, the prompt-injection defense layer , and the first production agent end-to-end as the pattern-setter for the team
• LLM Engineering at Depth: Set model selection, routing, and fallback policy across providers (AWS Bedrock, Anthropic) via the LLM gateway; own token-economics strategy including cost ceilings, runaway-loop kill-switches, and per-tenant cost attribution
• Knowledge Architecture: Direct the knowledge-graph and RAG strategy (Neo4j, embedding pipelines, hybrid retrieval), including the data contracts under which agents consume domain context securely in a multi-tenant environment
• MLOps / LLMOps: Define the observability standard , full-trace coverage (Langfuse), drift and quality monitoring, eval-gated CI/CD , and hold every agent release to it

Team Leadership & Capability Building

• Team Leadership: Lead and grow the AI engineering pod (senior and mid-level engineers); own technical performance, delivery quality, and the engineering bar for the track
• Agent Factory Cadence: Design and run the "Agent Factory" operating model , the standardized decision logic, templates, and review gates that compress agent delivery from months to weeks. The factory cadence is this role's defining success metric
• Mentorship & Standardization: Develop senior engineers toward lead level; codify patterns into internal frameworks and accelerators; contribute to Ciklum's AI Academy and practice-wide standards
• Recruitment: Own technical assessment design and final-round evaluation for AI engineering hires into the program

Requirements

• Track Record: 12+ years in software/AI engineering with 3+ years building LLM-powered systems in production, including at least one agentic platform or multi-agent system carrying real business transactions , not demos or PoCs
• AI Ecosystem: Expert-level Python; deep practical experience with at least one production agent framework (LangGraph, Claude Agent SDK, or equivalent) and the judgment to select between them; LangChain/LangSmith fluency; familiarity with the Prodigy framework is a significant advantage
• Evaluation Engineering: Demonstrated experience designing evaluation systems that gated real releases , golden datasets, field-level accuracy metrics, LLM-as-judge calibration, hallucination measurement , and defending those numbers to non-engineering stakeholders
• AI Security: Hands-on experience with prompt-injection defense, tool-call authorization, sandboxed execution (containers; Firecracker MicroVM exposure an advantage), and adversarial testing of LLM applications
• Architecture: Proven ability to author and defend ADRs for AI systems covering orchestration (Temporal or equivalent durable-execution platforms), multi-tenancy and identity (WorkOS or equivalent), knowledge graphs/vector retrieval (Neo4j, PGVector), and LLM gateway/routing (LiteLLM or equivalent)
• LLMOps: Production experience with tracing and cost observability (Langfuse or equivalent), eval-gated CI/CD, and per-tenant cost attribution at scale
• Leadership: Experience leading engineering teams of 4+ through ambiguous, milestone-driven deliveries; evidence of growing senior engineers and setting standards adopted beyond your own team
• Client-Facing Gravitas: Experience as the accountable technical voice in front of client CTOs/architecture boards, including negotiating acceptance criteria and handling adversarial technical scrutiny

Desirable

• Domain Expertise: Familiarity with Commercial Real Estate workflows (lease accounting, CAM reconciliation) or document-heavy regulated domains (legal, insurance, financial services)
• Compliance Exposure: Experience delivering AI systems under SOC 2, GDPR, or accessibility (Section 508) regimes; FedRAMP exposure a plus
• Platform Productization: Experience building AI platforms that were resold or white-labeled by the client (SDK design, developer experience, marketplace readiness)
• Community Standing: Publications, open-source contributions, or conference talks in the agentic AI space that strengthen Ciklum's technical credibility in client conversations

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 EdgeTech, 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.