About The Role
As the Head of AI Engineering, you will lead and scale our AI Engineering function across enterprise deployments. You will define the technical vision, build and mentor a high-performing team, and ensure that AI solutions move beyond proof-of-concept into reliable, production-grade systems that drive measurable business impact.
This is a
player-coach role — you will both guide strategy and remain close to the technology. You will oversee multiple enterprise engagements, shape system architecture standards, and ensure delivery excellence across all implementations.
You will own the success of AI delivery at scale — from technical direction and team capability to customer outcomes.
What You'll Do
AI Engineering Leadership
- Define and drive the overall AI engineering strategy, architecture standards, and best practices
- Build, mentor, and lead a team of AI engineers across multiple projects
- Establish scalable delivery processes, code standards, and quality benchmarks
- Create a strong engineering culture focused on ownership, speed, and impact
Enterprise AI Delivery Oversight
- Oversee end-to-end delivery of AI solutions across enterprise clients
- Ensure teams deliver from discovery → design → deployment → adoption successfully
- Act as escalation point for complex technical or delivery challenges
- Work closely with customers and stakeholders to ensure solutions align with real business needs
Agentic AI & System Architecture
- Define architecture patterns for multi-agent systems, orchestration, and AI workflows
- Guide teams in building reliable, production-ready agentic systems (LangChain, LangGraph, etc.)
- Ensure best practices in:
- LLM orchestration
- RAG pipelines
- evaluation & monitoring
- human-in-the-loop design
Technical Strategy & Innovation
- Stay at the forefront of AI advancements (LLMs, agents, infra) and translate them into practical use cases
- Evaluate tools, frameworks, and infrastructure to standardize across teams
- Drive internal innovation — reusable frameworks, templates, and tooling
Product & Cross-functional Impact
- Identify patterns across enterprise projects and translate them into product opportunities
- Partner with Product and Engineering leaders to influence roadmap
- Drive development of internal platforms, reusable assets, and accelerators
Operational Excellence
- Define KPIs for delivery success (adoption, performance, ROI)
- Ensure systems are scalable, observable, and maintainable
- Improve delivery speed through reusable components and standardized workflows
Requirements
Must-Haves
- 5+ years in software engineering, with 3-5+ years in AI/ML systems in production
- Proven experience leading engineering teams or technical organizations
- Deep hands-on experience with:
- LLMs (OpenAI, Anthropic, Gemini, OSS models)
- Prompt engineering, RAG, fine-tuning, evaluation
- Agentic AI systems (multi-step reasoning, tools, memory)
- Strong system design skills across APIs, cloud (AWS/GCP/Azure), and data systems
- Experience working with enterprise clients or complex environments
- Strong ownership mindset — accountable for outcomes, not just delivery
Benefits
- Hybrid work
- Health insurance
- Annual health check
- Laptop and other equipments
- Free snacks & drinks
- Weekly massage
- Grab transportation credit
- Education allowance
- Performance bonus
