Principal AI Engineer

Role : Principal AI Engineer

Company Name : WillWare Technologies

Location: India (Bengaluru) - 3(WFO)

Employment Type: Full Time (Overlapping EST)

Experience Level: Staff/Principal (8-14 years)

Working Hours: Comfortable with a daily overlap into US Eastern morning hours (8AM - 12 PM EST)

  What Were Looking For      

Engineering foundation

• 8-14 years of software engineering experience, with strong hands-on large-scale Python
• Working depth in at least one systems or backend language - Go, Rust, Java, or C/C++ - and the judgment to know when to reach for it
• Strong data structures and algorithms.
• Strong understanding of APIs, microservices, and system design
• Hands-on experience building and operating data pipelines and production-grade distributed systems.

Agentic AI and LLMs

• 2+ years of hands-on LLM engineering, with at least couple agentic system you designed and took to production
• Production experience with agent frameworks - LangGraph, Google ADK, CrewAI, Claude Agent SDK, or equivalent - and the fluency to move between them as the ecosystem evolves
• Experience building MCP (Model Context Protocol) servers and tool-calling interfaces
• RAG from first principles: chunking strategy, embeddings, vector and hybrid retrieval, reranking, and response validation
• Strong experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc. or cloud equivalents)
• Design of guardrails and reliability patterns - validators, policy checks, self-correction loops, deterministic fallbacks, circuit breakers, and rollback paths

Optimization

• Deep familiarity with token optimization and context-window management - context shaping, pruning, and compaction
• Latency and cost optimization through caching, model routing, batching, streaming, and parallel tool calls
• Performance testing and tuning systems against defined SLOs

Evaluation

• Experience building evaluation frameworks for LLM systems - offline eval sets, continuous online evaluation, and regression detection
• Instrumentation and traceability suitable for regulated enterprise environments using tools like LangSmith, Langfuse, etc.

Cloud

• Hands-on AWS: containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift) and orchestration (Step Functions)equivalents also valued
• Familiarity with CI/CD pipelines and DevOps practices
• Infrastructure as code with Terraform or CloudFormation, and mature CI/CD practice

Working traits

• Strong analytical problem-solving with a bias to ownership and urgency

• Clear cross-team communication, working directly with client stakeholders to translate business problems into technical roadmaps

• Able to work productively in ambiguity from system-level documentation and ramp quickly in unfamiliar codebases

  Good to Have      
  

• Experience with managed AI platforms - Amazon Bedrock, Vertex AI, Azure AI - paired with fluency in the underlying fundamentals

• Azure or GCP

  Roles & Responsibilities      
  

• Design and build agentic systems: Lead the architecture and implementation of tool-calling agents that combine retrieval, structured reasoning, and secure action execution with least-privilege access.

• Productionize LLM applications: Build retrieval pipelines, prompt synthesis, response validation, and self-correction loops, backed by rigorous evaluation.

• Own the full stack: Deliver the data pipelines, backend services, distributed compute, and orchestration layer that agentic systems depend on - not only the model invocation.

• Engineer for reliability and governance: Build validator models, adversarial test suites, and policy checks; enforce deterministic fallbacks and rollback strategies; instrument continuous evaluation.

• Optimize for cost and latency: Drive measurable improvements in token efficiency, response time, and unit economics against defined SLOs.

• Codebase ownership: Build, maintain, and review high-quality Python and SQL, with an emphasis on reusable components, scalability, and performance.

• Cloud integration: Deploy AI applications on AWS, Azure, or GCP with optimized resource usage and robust CI/CD.

• Cross-functional collaboration: Partner with product owners, data scientists, and business SMEs to define requirements and deliver impactful AI products.

• Mentoring and technical leadership: Set engineering standards and share knowledge across the team, raising the bar on AI and software engineering practice.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.