Senior AI Product Engineer
Skills
About the role
At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio.
We are currently looking for a dedicated Senior AI Product Engineer to join one of our clients' teams. If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you.
Key Responsibilities
AI Feature Delivery & Integration
Lead the end-to-end development of AI-powered features, from initial prototyping to production deployment.
Integrate LLMs and ML models into existing web/mobile applications and backend APIs.
Design "AI-first" user journeys, ensuring features like autocomplete, summarization, and intelligent search are intuitive and high-performing.
2. Prompt Engineering & Agentic Workflows
Craft, test, and optimize complex system prompts to ensure high-quality, safe, and consistent model outputs.
Build and manage Agentic workflows (using frameworks like LangChain, CrewAI, or AutoGen) to automate multi-step business processes.
Implement robust error-handling and "fallback" logic for non-deterministic AI responses to maintain a seamless UX.
3. Squad Collaboration (The "Product" Side)
Act as the AI subject matter expert within your Product Squad, helping PMs understand what is technically feasible vs. what is "AI hype."
Work closely with UX/UI designers to handle AI-specific design challenges (e.g., streaming text latency, "thinking" states, and user feedback loops).
Participate in agile ceremonies, contributing to grooming, planning, and rapid iteration.
4. Hybrid Implementation
Develop applications that can switch seamlessly between Cloud APIs (for speed/innovation) and On-Premises models (for data privacy and cost-efficiency).
Ensure that AI features are performant across different hosting environments without sacrificing user experience.
8+ years in Full-Stack or Backend Software Engineering.
3+ years of experience specifically building and shipping AI-integrated features.
Proven ability to work in an Agile/Scrum environment within a "Squad" structure.
Mastery of Python and/or TypeScript/JavaScript (React/Node.js).
Hands-on experience with LangChain, LlamaIndex, or Haystack.
Expertise in RESTful APIs, GraphQL, and working with Vector DBs (Pinecone, Weaviate).
Familiarity with Docker, Kubernetes, and deploying to AWS/Azure or local GPU environments.
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