Head of AI Engineering

ZENALYST

Enterprise Agentic Execution Layer

Bangalore, India|www.zenalyst.ai

Head of AI Engineering

Location:Bangalore

Type:Full-Time

Reports to:CEO

Exp:5+ Years

ABOUT ZENALYST

Zenalyst is building Indias first Enterprise Agentic Execution Layer an AI-native platform that automates complex, multi-step business workflows across finance, operations, and enterprise functions using autonomous AI agents. We are a Bangalore-based seed-stage startup backed by a powerhouse founding team with deep roots in Oracle, Jio, RedBus, SAP, Brillio, and Century Group.If you want to be at the frontier of enterprise AI not just building demos but shipping agents into production for real businesses this is the role.

THE ROLE

As Head of AI Engineering, you will own the entire technical execution of Zenalysts agentic AI platform. You will lead, build, and scale the engineering team across AI/ML, data engineering, and full-stack development. This is a hands-on leadership role you will architect systems, write code, train models, deploy agents, and make critical infrastructure decisions while mentoring a growing team.

You will report directly to the CEO and work alongside the CTO to translate product vision into a scalable, secure, enterprise-grade platform.

WHAT YOU WILL OWN

AI/ML Engineering:End-to-end ownership of model training, fine-tuning (LLMs, domain-specific models), evaluation pipelines, and inference optimization. Youll decide when to build vs. buy, when to fine-tune vs. prompt-engineer, and how to keep model quality high in production.

Agentic Systems:Design and deploy autonomous AI agents that execute multi-step enterprise workflows including tool use, memory, planning, error recovery, and human-in-the-loop orchestration.

Data Platform:Build robust data pipelines, vector databases, ETL/ELT workflows, and data infrastructure that feed the agentic layer. Ensure data quality, lineage, and governance for enterprise customers.

Engineering Team:Recruit, mentor, and manage the full engineering team (AI/ML engineers, data engineers, backend/frontend developers). Set engineering culture, code quality standards, sprint cadence, and delivery velocity.

Enterprise Delivery:Own the technical delivery for enterprise clients on-prem/cloud deployments, security compliance (ISO 27001), SLA management, and integration with client ERP/finance systems.

Platform Architecture:Design a scalable, multi-tenant platform architecture that can serve enterprise, mid-market, and MSME segments as the company scales toward its growth targets.

MUST-HAVE QUALIFICATIONS

5+ years of hands-on experience in AI/ML engineering, with demonstrated work in model training, fine-tuning, and production deployment of machine learning systems.

Deep expertise in building and deploying LLM-based applications RAG pipelines, agent frameworks (LangChain, CrewAI, AutoGen, or custom), prompt engineering, and tool-use orchestration.

Strong data engineering skills experience building production data pipelines, working with vector databases (Pinecone, Weaviate, Qdrant, etc.), and managing structured/unstructured data at scale.

Enterprise software experience you have built and shipped products for enterprise customers, understand compliance requirements, on-prem deployment, security, and integration with legacy systems (ERP, CRM, finance tools).

Proven leadership of engineering teams (minimum 45 engineers) hiring, mentoring, sprint planning, and delivery management.

Proficiency in Python, with working knowledge of cloud platforms (AWS/GCP/Azure), containerization (Docker, Kubernetes), and CI/CD pipelines.

Strong understanding of MLOps model versioning, A/B testing, monitoring, drift detection, and automated retraining workflows.

PREFERRED QUALIFICATIONS

Prior experience at a startup (seed to Series B) where you wore multiple hats and operated with high ownership and low hand-holding.

Track record of building AI products that generated measurable business outcomes not just research or PoCs, but deployed, revenue-generating systems.

Experience with finance/treasury/accounting domain data and workflows is a strong plus.

Familiarity with Indian enterprise IT landscape and ERP ecosystems (SAP, Tally, Oracle, custom ERPs).

Contributions to open-source AI/ML projects, published research, or technical blog posts demonstrating thought leadership.

Experience with multi-agent systems, agentic memory architectures, and autonomous workflow execution.

WHY ZENALYST

Founding-team proximity:Work directly with the CEO and CTO. Your decisions will shape the product, the team, and the company.

Real enterprise traction:This is not a pre-product company. We have a live customer, revenue, and a clear path to scale.

Meaningful equity:Competitive salary plus significant ESOP participation as an early engineering leader.

Frontier AI work:Build autonomous agents solving real problems for large enterprises not chatbots, not demos.

A-team colleagues:CTO (ex-Oracle/Jio/RedBus), CBO (ex-Century/Vatika), CSO (ex-SAP/Brillio), and a US strategic advisor.

COMPENSATION

Competitive base salary (benchmarked against Bangalore AI startup market) + meaningful ESOPs. Final package commensurate with experience and impact potential.

HOW TO APPLY

Send your resume along with a brief note covering: nagendra@zenalyst.ai (a) the most impactful AI system you built and deployed in production, (b) your experience leading engineering teams, and (c) why Zenalyst excites you.

Zenalyst Intelligent Execution, Autonomous Results