Staff AI Engineer

Location: Bengaluru - India (Hybrid) Experience: 10+ years Function: Applied AI / Generative AI Platforms & Applications Role Overview As a Staff AI Research Engineer , you will play a pivotal role in shaping the core AI platform, the Builder Studio abstractions, and the AI capabilities powering JazzX s enterprise applications . This is a hands-on Staff-level individual contributor role . You will work across platform, tooling, and applications designing and validating how foundation models, reasoning systems, and agentic workflows can be safely, reliably, and intuitively consumed by both engineers and non-technical users. Your work will directly influence: How AI systems are composed and deployed via low-code / no-code interfaces How customer-facing AI applications behave in production How JazzX balances power, safety, observability, and usability across its SaaS and PaaS offerings What You Will Do 1. Applied AI Research & Experimentation Explore and evaluate foundation models, reasoning models, multimodal models, and agentic workflows for enterprise use cases. Design experiments to understand model capabilities, limits, failure modes, and trade-offs. Assess how advanced AI techniques (RAG, dynamic prompting, RL, knowledge graphs, ontologies) can be abstracted safely into a Builder Studio experience . 2. Platform & System Architecture Design core AI platform components for: Model orchestration and routing Agent execution and state management Context, memory, and retrieval pipelines Evaluation, observability, and guardrails Define architectural patterns that work across platform APIs, low-code builders, and end-user applications . 3. Builder Studio Enablement (Low-Code / No-Code) Help design declarative abstractions and primitives that allow AI workflows to be composed visually or via configuration. Ensure that low-code experiences do not compromise correctness, safety, or performance . Work closely with UX, product, and platform teams to translate complex AI systems into intuitive building blocks. 4. First-Party Application Development Collaborate on building and evolving customer-facing enterprise AI applications using the JazzX platform and Builder Studio. Use these applications as real-world feedback loops to validate platform design decisions. Drive a strong dogfooding culture , ensuring the platform is battle-tested at scale. 5. Evaluation, Reliability & Safety Design and implement evaluation pipelines to continuously measure system quality. Develop strategies for hallucination mitigation, grounding, human-in-the-loop workflows, and deterministic guardrails. Ensure AI systems behave predictably in enterprise environments with high trust requirements. 6. Technical Leadership & Influence Serve as a Staff-level technical leader , influencing architecture and long-term platform direction. Mentor engineers and scientists on applied AI system design and AI-native engineering practices. Contribute to technical standards, RFCs, and cross-team architectural decisions. What We re Looking For Required Qualifications 10+ years of experience in applied AI, AI engineering, or AI-driven platform development. Strong hands-on experience building production-grade AI systems , not just prototypes or demos. Expert-level proficiency in Python , with a deep understanding of its ecosystem for building, scaling, and deploying production-grade AI services and orchestration layers. Deep experience working with AI foundation models (LLMs, reasoning models, multimodal models). Solid understanding of AI agents, orchestration frameworks, and evaluation methodologies . Experience with frameworks such as OpenAI SDK, LangChain, AutoGen, CrewAI , or equivalent. Knowledge of or experience with reinforcement learning, ontologies, knowledge graphs , or hybrid AI approaches. Preferred - Ph.D. or MS in Computer Science, AI, or a related field. Strong analytical and systems-thinking skills. What Sets You Apart You enjoy working across layers from models to platforms to end-user applications. You can translate cutting-edge AI capabilities into safe, usable, and scalable abstractions . You thrive in ambiguous environments and can define both the problem and the solution. You lead through technical influence and execution , not hierarchy. You care deeply about production readiness, reliability, and user trust .