Lead Fullstack AI Engineer

Overview :
TekWissen is a global workforce management provider throughout India and many other countries in the world. The job opportunity described below is for one of our clients, who has developed a core competence in creating and deploying cost-effective capabilities using an offshore-centric business model. Position: Lead Fullstack AI Engineer Location: Remote Job Type: Contract
Duration: 6 Months Work Type: Remote
Job Description:

• We are seeking an elite Lead Full Stack AI Engineer to design and build the operator control plane for our enterprise AgenticOps platform.
• In this role, you will connect real-time web interfaces with asynchronous multi-agent backends-turning complex agent reasoning, dynamic network topologies, and automated remediation runs into intuitive, transparent interfaces for IT and SOC operators.
• You will bridge frontend performance with modern AI frameworks, NVIDIA/Cisco integrations, and open-source tooling.

Core Responsibilities:

• Operator Cockpit & HITL Control: Build the primary AgenticOps console with real-time telemetry streaming, interactive multi-agent reasoning traces, execution dry-runs, and human-in-the-loop (HITL) approval/override controls.
• Dynamic Topology & DAG Visualization: Develop high-performance WebGL/canvas-based visual interfaces to render large-scale enterprise network maps, asset dependencies, and live multi-agent execution graphs without UI lag.
• Low-Latency Streaming Pipelines: Engineer bidirectional streaming protocols (WebSockets, SSE, gRPC-Web) to handle real-time agent thought streams, tool invocation payloads, and live terminal outputs.
• BFF & Edge Middleware: Build performant backend-for-frontend (BFF) layers in Go, Python (FastAPI), or TypeScript, implementing session state persistence, token caching, SAML/OIDC authentication, and fine-grained RBAC.
• AI Tooling & Ecosystem Integration: Connect the UI layer to agent runtimes, open-source automation tools (OpenClaw, Browser-Use), and model endpoints powered by NVIDIA NIMs, vLLM, and local SLMs.
• AI-Augmented SDLC: Utilize AI-assisted development workflows, automated component scaffolding, synthetic UI testing, and continuous eval pipelines to accelerate delivery.

Required Qualifications:

• Experience & Track Record: 8+ years building enterprise-grade full-stack web applications, with 3+ years focused on AI/LLM-native interfaces, observability platforms (APM/SIEM), or network operations tooling.
• Frontend Architecture: Deep mastery of TypeScript, React / Next.js, Tailwind CSS, state management (Zustand, TanStack Query), and rendering optimization for real-time streaming data
• Graph & Canvas Visualization: Production expertise with canvas/SVG/WebGL visualization libraries (React Flow, Cytoscape.js, PixiJS, D3.js) for large-scale hierarchical graphs and multi-step agent reasoning trees.
• AI & Agentic Ecosystem: Hands-on experience with modern agent frameworks (LangChain, LangGraph, Vercel AI SDK), open-source agentic tools (OpenClaw, Browser-Use), and consuming endpoints from NVIDIA NIMs, vLLM, or Ollama.
• Streaming & Real-Time Protocols: Production fluency with SSE, WebSockets, and chunked streaming, managing partial token rendering and optimistic UI states under network latency.
• UX for Autonomous Systems: Strong design intuition for non-deterministic software: progressive disclosure of reasoning, confidence/risk scoring, before-and-after diff previews, and safety-critical confirmation workflows.

Mandatory:
Experience

• 8+ years building enterprise-grade full-stack web applications
• 3+ years on AI/LLM-native interfaces, observability platforms (APM/SIEM), or network operations tooling

Frontend

• TypeScript, React / Next.js, Tailwind CSS
• State management: Zustand, TanStack Query
• Rendering optimization for real-time streaming data

Graph & Visualization

• Production experience with at least one of React Flow, Cytoscape.js, PixiJS or D3.js (canvas/SVG/WebGL)
• Rendering large hierarchical graphs and multi-step agent reasoning trees

Real-Time Streaming

• SSE, WebSockets and chunked streaming
• Partial token rendering and optimistic UI under network latency

Backend / BFF

• Backend-for-frontend layers in Go, Python (FastAPI) or TypeScript
• SAML/OIDC authentication, RBAC, session state and token caching

AI & Agentic Ecosystem:

• Agent frameworks: LangChain, LangGraph or Vercel AI SDK
• Consuming model endpoints from NVIDIA NIMs, vLLM or Ollama

UX for Autonomous Systems

• Human-in-the-loop (HITL) approval/override workflows
• Progressive disclosure of reasoning, confidence/risk scoring, diff previews and safety-critical confirmations

Good to Have (Optional)

• gRPC-Web
• OpenClaw, Browser-Use
• Local SLM deployment
• NVIDIA/Cisco platform integrations
• AI-assisted SDLC: component scaffolding, synthetic UI testing, continuous eval pipelines

Required Competencies

• Must possess excellent communication skills oral and written
• Must possess knowledge of latest technology trends
• Must be a keen learner should be able to drive "Self Learning"
• Must practice principle of "First Time Right"
• Must have an Eye for Details
• Must have high Customer Orientation
• Must be adaptable to working in multiple / matrix work environment
• Must possess good systems thinking
• Must possess good negotiation, analytical and interpersonal skills. Good leadership & team
• player qualities.
• High on personal integrity with ability to establish relationships and work in teams and should be able to influence stakeholders. Should poses independence, robust ethics and resilience.

Years of Experience:

• 10+ years of relevant work experience with a reputed organization.

Educational Qualification:

• ME (IT, Computer), BE (IT, Computer), MCA, MSC-IT, BCA

TekWissen Group is an equal opportunity employer supporting workforce diversity