Full stack engineer developing and scaling generative AI applications at PwC. Collaborating across teams to enhance software solutions and mentor junior engineers while maintaining high standards.
About the role
- Head of AI Engineering leading AI Engineering function across enterprise deployments. Define strategy, mentor team, oversee delivery of AI solutions.
Responsibilities
- 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
- 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
- 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
- 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
- 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
- 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
- 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
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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