16 hours ago
Pune, IndiaSenior
Responsibilities
- Build production AI and agentic workflows end to end, from PRD and architecture through implementation, evaluation, release, and production iteration.
- Design agent orchestration with tool and API invocation, planning, routing, state, memory, retries, fallbacks, timeouts, and human-in-the-loop checkpoints.
- Own retrieval and context engineering, including corpus onboarding, parsing, chunking, embeddings, hybrid search, reranking, metadata filtering, query transformation, permissions, freshness, and incremental indexing.
- Select, tune, route, and evaluate models based on quality, latency, and cost; manage prompts, structured outputs, context strategies, and applicable fine-tuning or distillation.
- Build evaluation harnesses with golden datasets, offline evaluation, calibrated LLM-as-judge workflows, regression suites, and online quality monitoring.
- Design, build, and maintain reusable SDKs, shared services, templates, reference implementations, documentation, and component libraries for internal and partner engineers.
- Integrate AI systems with enterprise ERP, CRM, support, services delivery, knowledge, and data platforms.
- Implement production engineering practices including observability, tracing, token and cost telemetry, quality dashboards, caching, batching, streaming, infrastructure as code, environment promotion, secrets management, and testing.
- Participate in operational support, incident remediation, post-incident reviews, code reviews, and design reviews.
- Set engineering standards for the AI Centre of Excellence and mentor subsequent hires and partner engineers.
Requirements
- 6+ years of professional software engineering experience, including 2+ years building and operating production LLM or GenAI systems with real users and operating costs.
- Excellent Python skills and working competence in at least one additional language such as TypeScript, Go, or Java.
- Production experience building, measuring, and improving RAG or hybrid search systems.
- Experience with agent orchestration frameworks such as LangGraph, LlamaIndex, Semantic Kernel, Google ADK, Strands, CrewAI, or equivalent.
- Strong AWS and/or GCP experience, including managed AI services, compute, serverless, networking, IAM, and managed data services.
- Experience with API design, enterprise integration, OAuth 2.0 or OIDC, service-to-service authentication, and delegated or on-behalf-of access.
- Experience with containerization, infrastructure as code, CI/CD, and disciplined software testing.
- Ability to define and measure quality for subjective AI tasks and act on evaluation results, with strong cost and latency awareness.
- Strong written communication skills for design notes, documentation, and status reporting, plus comfort with ambiguity and shifting priorities.
- Preferred experience with production-scale vector or hybrid search infrastructure such as OpenSearch, pgvector, Vertex AI Search, Elasticsearch, Pinecone, or Weaviate.
- Preferred experience with evaluation and observability tools such as LangSmith, Langfuse, Phoenix, Braintrust, Ragas, or DeepEval.
- Preferred experience with multi-tenant SaaS, ERP, manufacturing or supply-chain data, classical ML and MLOps, fine-tuning, model serving, internal platforms or SDKs, and open-source AI engineering contributions.
Benefits
- Programs supporting health and well-being and work-life balance.
- Opportunity to join a growing business entering an expansion and transformation phase.
- Collaborative culture with support from smart and hardworking colleagues.
- Growth and advancement opportunities with idea-sharing prioritized over hierarchy.
- Compensation packages based on experience and desired skill set.
Tech Stack
Categories
About QAD, Inc.
QAD builds cloud-based ERP and supply chain software for manufacturing companies, with offerings like QAD Adaptive ERP and the Redzone Connected Workforce platform, sold primarily by subscription with professional services. Its products target mid-market firms across automotive, industrial, food & beverage, life sciences, and consumer goods, embedding workflow and shop-floor capabilities. Founded in 1979 and headquartered in Miami, QAD is privately held and owned by Thoma Bravo.