AI Engineering Manager (AI)

TL;DR

AI Engineering Manager (AI): Leading R&D on LLM-based agentic workflows, data intelligence, and AI-first products with an accent on technical design, end-to-end execution, and delivery of agentic systems. Focus on integrating AI-native capabilities with hirify.global’s cloud-native data platform.

Location: Bangalore

Company

hirify.global’s AI-powered data unification and management capabilities transform siloed data from disparate sources into unified, trusted, and interoperable data.

What you will do

• Deliver hands-on engineering management for an AI team of Data Scientists, ML Engineers, UI/Integration Engineers, and ML SDETs.
• Own agentic AI systems that plan, reason, use tools/APIs, maintain memory/context, self-correct, and execute multi-step workflows autonomously.
• Design, implement, and productionize end-to-end RAG pipelines, balancing chunking, embeddings, indexing, latency, and cost.
• Build/refine LLM/ML models for entity resolution, semantic search, matching, and data unification; identify automation opportunities for scalability.
• Design A/B experiments to evaluate agent responses, grounding, and quality; evolve memory architectures, vector search, and context management.

Requirements

• Proven track record leading and motivating high-performing AI/ML teams in ambiguous, fast-paced environments.
• Deep hands-on experience building and productionizing agentic/multi-step AI workflows.
• Expertise in LLMs, RAG/retrieval architectures, foundation models (embeddings, transformers), vector search, semantic similarity, and prompt engineering.
• Strong product intuition: Translate business problems into scoped ML/LLM solutions with measurable user impact.
• Ownership of production ML code in Python, including cloud deployments (AWS Bedrock, SageMaker, Azure AI Studio).
• Experience with graph memory, MCP protocol (or equivalent), and knowledge reasoning engines.

Nice to have

• Hands-on experience with data governance, security best practices, MLOps and LLM observability.
• Track record contributing to enterprise-scale SaaS or AI/ML products.
• Familiarity with Kubernetes, containerized deployment, and scalable APIs.

Culture & Benefits

• Comprehensive Group medical insurance including your parents with additional top-up options.
• 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
• 01 week of additional off as recharge week every year globally
• Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement