Forward Deployed Engineer

Location: Mumbai, India | On-site. This role represents a foundational position in Supervity's Forward Deployed Engineering pod, targeting engineers who excel at the intersection of software engineering, sales strategy, and systems architecture. The organization characterizes this as an "elite, high-visibility role" for "hybrid technologists" who operate where advanced AI meets complex legacy enterprise systems. The engineer functions as "the ultimate unblocker," working directly with executive leadership to bridge proprietary AI technology with Fortune 500 client ecosystems, operating "with the autonomy of a startup founder and the technical rigor of a staff engineer." Core Responsibilities: Lead technical discovery sessions with enterprise C-suites and functional directors; identify operational bottlenecks and translate them into AI architectures; serve as technical authority during sales cycles. Architect and deploy complex AI Command Centers and multi-agent workflows; compress idea-to-production timelines into "rigorous 5-day sprints"; write production-quality code integrating Supervity's platform with legacy systems (ERPs, SAP, Coupa) using APIs, WebSockets, and custom data pipelines. Codify field insights into reusable architectural patterns; resolve AI hallucinations and optimize vector search latencies; ensure human-in-the-loop governance integration. Required Competencies: Demonstrated ability to write "highly reliable, production-ready code under significant client pressure"; professional proficiency in Python, TypeScript, or similar backend frameworks (FastAPI, Node.js); experience with GCP ecosystem (Vertex AI, Cloud Run) and containerization (Docker). "Exceptional, highly polished communication skills"; ability to explain complex concepts to executives while collaborating with technical DevOps teams. "Founder-like mentality characterized by extreme ownership"; comfortable operating in ambiguous environments. Foundational understanding of modern machine learning paradigms and LLM orchestration (LangChain, RAG pipelines); data engineering principles knowledge (PostgreSQL, Vector Databases). The role operates on a "highly flexible, asynchronous schedule" designed to accommodate global clients while eliminating permanent late-night shifts.