AI Engineer Job at Expert Technology Services, New Jersey

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  • Expert Technology Services
  • New Jersey

Job Description

Job Details:

Job Title: Gen AI Leads/Architect

Job Location: NYC, NY (Onsite)

Employment type: 6 Months +

Contract Duration: long term

Rate: $75/hr. C2C

Job Reference Number (if applicable): NA

Willing to work Onsite: yes

Client : Zensar Technology

Job Title: Gen AI Leads/Architect

Location: NYC, NY (Onsite)

Employment Type: (Full-time or contract)

Duration: Contract

Evaluation stages:

  • Stage 1 - Technical screen: Walk us through a live agent system you built
  • Stage 2 - Architecture discussion: Given a business problem, design an agent solution on the spot
  • Stage 3 - Stakeholder simulation: Present your approach to a non-technical executive audience



About VLink: Started in 2006 and headquartered in Connecticut, VLink is one of the fastest growing digital technology services and consulting companies. Since its inception, our innovative team members have been solving the most complex business, and IT challenges of our global clients.



Job Description:



Job Description :

Key Responsibilities

Delivery & Architecture

  • Own end-to-end delivery of AI-native programs - from architecture through production deployment
  • Design and build multi-agent orchestration systems using LangChain, LangGraph, CrewAI, or equivalent
  • Integrate agent systems with enterprise surfaces: APIs, ERPs, CRMs, data platforms - not toy datasets
  • Define agent topology: tool routing, memory strategy, state machines, fallback handling



Agentic Coding & Development

  • Run agentic coding workflows using Claude Code, Cursor, OpenAI Codex, or equivalent CLI tools
  • Lead projects where AI writes significant portions of the codebase - and you guide, review, and ship it
  • Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
  • Debug non-deterministic agent outputs systematically - not by gut feel



Client & Stakeholder Engagement

  • Translate business problems into agent architectures for global CXO-level stakeholders
  • Run discovery workshops, solution reviews, and delivery cadences with client teams
  • Prepare and present technical proposals, POC plans, and roadmaps - own the story end-to-end



Team & Practice

  • Mentor junior AI engineers; raise AI engineering quality across the delivery team
  • Stay current: evaluate new models, frameworks, and tooling before the hype catches up
  • Contribute to internal knowledge bases, reusable frameworks, and accelerators



Skills

Agent Orchestration
LangChain, LangGraph, CrewAI - not just conceptual

Agentic Coding Tools
Claude Code CLI, Cursor, OpenAI Codex, Copilot

RAG & Vector Stores
Chroma, Weaviate, Pinecone - knows where RAG breaks

LLM APIs & SDKs
Anthropic, OpenAI, Gemini - prompt design, tool use

Python / TypeScript
Primary languages for agent + backend development

LangSmith / Observability
Tracing, evaluation, debugging agent runs

Cloud Platforms
Azure, AWS, GCP (at least one) - deployment, infra, managed services

API & System Integration
REST, gRPC, Kafka - enterprise integration patterns

MCP / Shared Context
Model Context Protocol, CLAUDE.md, Beads

Agent Evaluation
Testing non-deterministic outputs, guardrails, evals

CI/CD & DevOps
Git, containers, pipelines - agents need to ship

Client Communication
Can present architecture to a CXO without jargon



What You Must Have Actually Done
Not just what you know. What you have shipped.

  • Deployed 2 3 agent-based systems in production - stateful, multi-step, real users
  • Used LangGraph for multi-agent orchestration with memory, tool routing, and state management
  • Built projects where AI (Claude Code, Codex, Cursor) wrote significant portions of the code
  • Implemented RAG pipelines end-to-end - chunking, embedding, retrieval, re-ranking, evaluation
  • Integrated agents with real enterprise APIs - not just OpenAI playground or sample data
  • Debugged a production agent failure - and fixed it without blaming the model
  • Can articulate when NOT to use agents - that is how we know you have built things



Bonus - Real Differentiators

  • Experience with Claude Code CLI in team environments (CLAUDE.md, shared context, multi-session flows)
  • Familiarity with LangSmith for agent tracing, evaluation pipelines, and debugging at scale
  • Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
  • QA/testing mindset for agents - systematic evaluation of non-deterministic outputs
  • Background in IT services or consulting - managing client expectations while building
  • Experience with SLMs, fine-tuning, or on-device/edge agent deployment



What We Are Not Looking For

  • Someone who lists LLMs on a resume but has only called the API in a Jupyter notebook
  • AI enthusiasts whose hands-on experience is less than a year old
  • People who explain everything in terms of frameworks they have never deployed
  • Consultants who can only narrate what others have built

Job Tags

Full time, Contract work

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