Lead Fullstack AI Engineer
Tekwissen India
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
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