NewNew: The enterprise guide to Agentic AI — 24 min read.

Read →
Agentic AI · Talent

Agentic AI engineers who ship to production.

LangGraph, LangChain, tool-use, multi-agent orchestration, RAG, evals and guardrails — engineers who have already shipped autonomous voice, chat and email agents on live CCaaS.

48 hrs
3 vetted profiles delivered
Prod
All engineers have shipped agents live
2 weeks
Typical time-to-billable
Role-specific
Why teams book Talent with Pronix
  • 48 hrs — 3 vetted profiles delivered
  • Agent architects
  • Engineers & platform
  • Evals, guardrails & observability
Book your working session

30 minutes, no slides. A senior delivery lead reviews your stack and gives you a concrete pilot outline.

Trusted by enterprise CX & digital teams
  • LangGraph
  • LangChain
  • OpenAI
  • Anthropic
  • AWS Bedrock
  • Azure OpenAI
What you get

A working pilot in 90 days — not a 40-page slide deck.

01
Agent architects

Multi-agent graph design, tool schemas, memory strategies, RAG pipelines and cost/latency budgets for voice and digital contact-center agents.

02
Engineers & platform

Python/TypeScript engineers on LangGraph, LangChain, LlamaIndex, Bedrock, Azure OpenAI, Vertex — plus vector stores (pgvector, Pinecone, OpenSearch).

03
Evals, guardrails & observability

LLM-as-judge evals, deterministic regression suites, red-teaming, Trust Layer / Guardrails AI and production tracing with LangSmith, Langfuse or Arize.

Proof

Three agentic engineers landed inside a week and shipped a multi-agent claims triage to production in 90 days — with evals we could defend to risk.

VP of AI Engineering — US insurer
3 engineers in 7 days · Multi-agent triage live in 90 days
FAQ

Questions buyers ask us first.

What backgrounds do your agentic engineers have?
Most are senior Python/TypeScript engineers with 3–8 years in ML/LLM systems and at least one shipped agentic system in production — not just notebook demos.
Which frameworks and models do they work in?
LangGraph, LangChain, LlamaIndex, CrewAI, custom orchestration; OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex, open-weights via vLLM.
Contract, contract-to-hire or managed pod?
All three. Individual contractors, embedded pods, or fully managed pods with an architect, engineers, an evals lead and shared SLA.
How do you evaluate agent quality before production?
Every engagement ships with an evals harness — task success, tool-use accuracy, hallucination rate and cost per successful task — gated in CI before any agent is promoted.
How do you handle governance and data protection?
Trust Layer / Guardrails AI, prompt-injection defenses, PII redaction, model routing rules, evaluation gates and security-cleared engineers on every SOW.

Ready to see it in your stack?

30 minutes with a delivery lead. Your architecture, your KPIs, a concrete pilot outline you can defend internally.

Book a 30-min working session
Book a 30-min working session