Strategic Role Overview
Supervity is actively constructing the founding tier of its Forward Deployed Engineering pod in Mumbai. This is an elite, high-visibility role designed for hybrid technologists who thrive at the absolute intersection of sophisticated software engineering, executive sales strategy, and complex systems architecture. The enterprise transition from static software to autonomous Agentic AI represents the most critical technological shift of the current decade. However, the vast majority of these integrations fail due to a lack of technical empathy and execution capability.
The Forward Deployed AI Engineer operates as the ultimate unblocker. Working directly alongside Supervity's executive leadership, this role serves as the human bridge connecting the company's highly advanced, proprietary AI Employees with the unstructured, highly regulated realities of Fortune 500 client ecosystems. Deployed to the front lines of the most strategic, multi-million-dollar commercial engagements, this engineer is fundamentally responsible for making the technology work. They will map complex customer workflows, architect bespoke AI solutions, write the production-grade code required to integrate those solutions, and drive the deployment to live production status at unprecedented speeds. Operating with the autonomy of a startup founder and the technical rigor of a staff engineer, this role does not tolerate being hidden behind ticketing systems; it demands continuous, direct client engagement and absolute ownership of the implementation lifecycle.
Core Operational Responsibilities
The primary mandate of the Forward Deployed AI Engineer extends far beyond standard software development. The responsibilities encompass the entire lifecycle of an enterprise deployment, beginning with the initial executive discovery phase and culminating in the stabilization of live, production-scale AI systems.
- Customer Zero deployments and sales engineering: Lead technical discovery sessions alongside Supervity leadership, interfacing directly with enterprise C-suites and functional directors to identify operational bottlenecks and translate them into high-ROI Agentic AI architectures. Act as the definitive technical authority during the sales cycle, conducting technical deep-dives and executive demonstrations that directly contribute to closing major enterprise contracts.
- Rapid prototyping and full-stack execution: Utilize Supervity’s proprietary frameworks and the Google Cloud Platform ecosystem to architect and deploy complex "AI Command Centers" and multi-agent workflows, consistently striving to compress the idea-to-production lifecycle into rigorous 5-day sprints. Write custom, production-quality code to seamlessly integrate Supervity’s AI platform with deeply entrenched legacy enterprise systems, such as custom ERPs, SAP, or Coupa, utilizing secure API connectors, WebSockets, and customized data pipelines.
- Critical architectural feedback loop: Systematically codify field insights, identifying reusable architectural patterns and feeding them back to the core product engineering team to continuously refine the Supervity platform. Possess real-time debugging capabilities necessary to resolve hallucinations, optimize vector search latencies, and ensure that human-in-the-loop governance controls are flawlessly integrated into the final client product.
Competency Matrix and Prerequisites
While comprehensive training on Supervity's proprietary artificial intelligence technology stack will be provided, candidates must possess a highly specific foundational profile. The evaluation focuses heavily on technical velocity, communication prowess, and operational agency.
Competency Domain: Technical & Coding Foundations
- Must possess a profound builder's mindset with a demonstrated ability to write highly reliable, production-ready code under significant client pressure.
- Professional proficiency in languages such as Python, TypeScript, or similar backend frameworks (e.g., FastAPI, Node.js) is non-negotiable.
- Experience with modern cloud architectures, particularly the GCP ecosystem (Vertex AI, Cloud Run), and containerization methodologies (Docker) is required.
Competency Domain: Communication & Stakeholder Management
- Exceptional, highly polished communication skills are mandatory.
- The engineer must possess the socio-technical empathy to explain complex algorithmic concepts to executive leadership while simultaneously collaborating with deeply technical client DevOps teams.
- The ability to articulate business value, manage expectations, and conduct authoritative sales engineering presentations is critical.
Competency Domain: Problem Decomposition & Agency
- Must exhibit a "founder-like" mentality characterized by extreme ownership.
- Requires the ability to operate comfortably in highly ambiguous environments, rapidly identify the root cause of integration blockers, and make pragmatic trade-offs between architectural purity and deployment speed.
Competency Domain: AI & Systems Architecture
- A foundational understanding of modern machine learning paradigms, LLM orchestration (e.g., LangChain, RAG pipelines), and data engineering principles (PostgreSQL, Vector Databases) provides a significant competitive advantage.
Operational Logistics
- Based out of Mumbai, India.
- The role operates on a highly flexible, asynchronous schedule designed to maximize productivity and accommodate strategic overlap with global clients, entirely removing the necessity for permanent or extreme late-night shifts.