It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
We are looking for a Head of Engineering to lead our AI capability, spanning AI platforms, machine learning systems, and emerging agentic AI architectures. This role is responsible for driving end-to-end solutioning—from client discussions and problem framing to execution strategy and production delivery.
You will operate at the intersection of client advisory, technical architecture, and execution leadership, building scalable foundations that power advanced AI and autonomous systems.
1. Client Advisory & Problem Framing
Lead senior-level client conversations to identify opportunities across data, AI, and agentic workflows
Translate ambiguous business problems into structured AI/data solution blueprints
Act as a trusted advisor on AI transformation roadmaps, including platform and operating model design
Present architectures, trade-offs, and execution strategies to technical and non-technical stakeholders
2. Data & AI Foundations
Define and drive architecture for modern data platforms (data lakes, lakehouses, real-time pipelines)
Build scalable ML and AI foundations including feature stores, training pipelines, and inference systems
Establish reusable frameworks, accelerators, and reference architectures
Ensure strong governance across data quality, lineage, security, and compliance
3. Agentic AI Systems
Lead design and implementation of agentic AI systems (LLM-based agents, RAG pipelines, multi-agent orchestration)
Define patterns for tool use, memory, reasoning workflows, and human-in-the-loop systems
Evaluate and integrate emerging GenAI technologies into production-grade solutions
Drive experimentation → industrialization of agentic use cases
4. Execution Strategy & Delivery Leadership
Own end-to-end delivery: discovery → PoC → MVP → scaled production
Build and lead cross-functional teams across data engineering, ML engineering, and AI engineering
Define delivery plans, milestones, and measurable outcomes
Manage risks, dependencies, and client expectations in complex engagements
5. Engineering Excellence & MLOps
Establish best practices across CI/CD, MLOps, LLMOps, and observability
Ensure robustness in model performance, monitoring, retraining, and lifecycle management
Drive standards for reproducibility, evaluation, and system reliability
6. Capability Building & Influence
Build internal capability across AI foundations and agentic systems
Mentor engineering leaders and shape technical culture
Contribute to thought leadership, GTM assets, and reusable IP
Influence senior stakeholders across client and internal ecosystems
15 to 20 years in engineering across data, platforms, and AI/ML systems
5+ years in leadership roles managing large, distributed engineering teams
Strong experience in data platforms (batch + streaming), cloud ecosystems (AWS/Azure/GCP)
Deep expertise in ML systems, MLOps, and production AI architectures
Hands-on experience with Generative AI and LLM-based systems (RAG, agents, orchestration frameworks)
Proven ability to lead client-facing engagements and drive delivery from concept to production
Excellent communication and executive stakeholder management skills
Experience in consulting / AI services organizations
Exposure to building agentic workflows in enterprise settings
Familiarity with tools like LangChain, LlamaIndex, vector databases, orchestration frameworks
Experience across multiple industries and large-scale transformations
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
India: HiringsupportIndia@fractal.ai
Outside India: HiringsupportROW@fractal.ai
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