Engineering Manager

Job highlights

• . LLM Engineering Fine-Tuning: Practical experience with fine-tuning toolchains (Hugging Face,PEFT / LoRA,Axolotl,DeepSpeed),alignment (DPO / RLHF),quantization,and agent frameworks (LangChain,LangGraph,DSPy)
• Required Qualifications: .
• Experience Requirements
• Required Competencies
• Good leadership team player qualities

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: Engineering Manager

Location: Remote

Job Type: Contract
Duration: 6 Months

Work Type: Remote

• Engineering Manager Principal Systems Architect (AgenticOps Core)
• We are seeking a hands-on Engineering Manager Principal Systems Architect to serve as the technical anchor, customer-facing architect, and engineering leader for our enterprise AgenticOps platform.
• In this player-coach role, you will lead a specialized engineering pod building productiongrade autonomous runtimes for enterprise IT and SecOps. You will own the architectural blueprint, write production code, fine-tune models, and work directly with enterprise customers and technical partners across NVIDIA and Cisco.

Core Responsibilities:

• Architecture Hands-On Engineering: Lead, design, and personally code an event-driven, high-throughput multi-agent platform in Golang for closed-loop IT self-healing and SecOps containment.
• Customer Partner Advisory: Serve as primary technical lead for enterprise clients and design partners (Cisco, NVIDIA). Lead deep-dive architectural workshops and translate complex operational workflows into multi-agent specifications.
• NVIDIA AI Stack Inference Acceleration: Architect GPU-accelerated inference pipelines using NVIDIA NIM microservices, NeMo Framework/Guardrails, and TensorRT-LLM across DGX clusters, hybrid cloud, and edge.
• Model Adaptation Fine-Tuning: Lead data curation and fine-tuning pipelines (PEFT, LoRA/QLoRA, distillation) to adapt open-weight models (Llama, Mistral, Qwen, DeepSeek) for IT/SecOps tasks.
• Agent Frameworks Open-Source Ecosystem: Build durable agent runtimes using LangChain, LangGraph, or custom state machines. Leverage open-source agentic and execution tooling (e.g., OpenClaw, Nemoclaw) and local inference engines (vLLM, Ollama).
• Safety, Governance AI-Native SDLC: Engineer deterministic safety harnesses (dry-run preflights, blast-radius containment, rollbacks) and establish an AI-augmented SDLC (agentic PR reviews, synthetic evals, LLM-as-a-judge).
• Team Leadership Integration: Recruit, mentor, and lead an elite pod; enforce rigorous code reviews, evals, and OpenTelemetry observability while integrating with enterprise substrates (Cisco Cloud Control, Intersight, Nexus, Splunk).

Required Qualifications:

• Experience Scope: 10+ years architecting scalable distributed systems and backend infrastructure, with 3+ years as a hands-on player-coach leading engineering teams.
• Customer-Facing Acumen: Proven ability to interface with enterprise architects and leaders on technical discovery, system architecture, and complex deployments.
• Core Languages: Deep production mastery of Go (Golang) for high-concurrency, low-latency microservices; strong proficiency in Python for AI/ML pipelines and orchestration.
• NVIDIA AI Stack: Hands-on experience with NVIDIA AI Enterprise, NIMs, NeMo Guardrails, TensorRT-LLM, and Triton Inference Server on modern GPU architectures.
• LLM Engineering Fine-Tuning: Practical experience with fine-tuning toolchains (Hugging Face, PEFT/LoRA, Axolotl, DeepSpeed), alignment (DPO/RLHF), quantization, and agent frameworks (LangChain, LangGraph, DSPy).
• Open-Source Tooling: Experience self-hosting open models (vLLM, Ollama) and integrating open-source agentic/browser automation tools (OpenClaw, Browser-Use).
• Distributed Systems Safety: Strong background in event-driven streaming (Kafka, NATS, gRPC), vector/graph databases (pgvector, Qdrant, Neo4j), and zero-trust safety execution guardrails.
• Domain Fluency: Working knowledge of enterprise IT fabrics (SDN, data center networking), observability platforms (Splunk, ThousandEyes), and SOC incident lifecycles.

Leadership Role:

• Engineering Manager, Principal Systems Architect, Player-Coach
• Hands-on Technical Leadership, Team Mentoring, Code Reviews
• Customer-Facing Architect, Technical Discovery, Architectural Workshops

Core Languages Backend

• Golang (Go), Python
• Distributed Systems, Event-Driven Architecture, Microservices
• High-Concurrency, Low-Latency, High-Throughput
• gRPC, Kafka, NATS

Agentic AI

• AgenticOps, Multi-Agent Systems, Autonomous Agent
• LangChain, LangGraph, DSPy, Custom State Machines
• OpenClaw, Browser-Use
• Closed-Loop Automation, IT Self-Healing, SecOps Containment

NVIDIA AI Stack:

• NVIDIA AI Enterprise, NVIDIA NIM, NeMo Framework, NeMo Guardrails TensorRT-LLM, Triton Inference Server
• DGX, GPU-Accelerated Inference

LLM Engineering Fine-Tuning

• Fine-Tuning, PEFT, LoRA/QLoRA, Distillation, Quantization
• DPO, RLHF, Alignment
• Hugging Face, Axolotl, DeepSpeed
• Open-Weight Models (Llama, Mistral, Qwen, DeepSeek)
• vLLM, Ollama, Self-Hosted LLMs

Data Storage

• Vector Databases (pgvector, Qdrant), Graph Databases (Neo4j)

Safety Governance

• Zero-Trust, Safety Guardrails, Dry-Run Preflight
• Blast-Radius Containment, Rollbacks
• LLM-as-a-Judge, Synthetic Evals, Agentic PR Reviews, AI-Native SDLC

Observability Enterprise Integration

• OpenTelemetry, Splunk, ThousandEyes
• Cisco Cloud Control, Intersight, Nexus
• SDN, Data Center Networking, SOC Incident Lifecycle.

Experience Requirements

• 10+ Years in Distributed Systems / Backend Infrastructure
• 3+ Years Player-Coach / Team Lead
• Enterprise Customer Engagement (Cisco, NVIDIA partners)

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.