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

• 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

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.