Full-Stack AI Engineer (Agentic Solutions)

Whiz Global LLC; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Whiz Global LLC is seeking a Senior Full-Stack AI Engineer to design, build and deploy agentic AI solutions remotely. You will lead end-to-end development of coding agents, orchestration, data pipelines, and evaluation across Azure-based tooling and vector stores.

Ideal candidates have 6+ years in software engineering, with 2+ years in LLM/agent solutions, prompt design and CI/CD—plus strong communication for agile collaboration with business teams.

Qualifications

• Strong full-stack engineering in Python and/or C#/.NET with API and integration development.
• Hands-on delivery of LLM/agent applications: prompt design, function and tool calling, RAG and workflow orchestration.
• Experience with at least one of Azure AI Foundry, Copilot Studio or Microsoft Agent Framework.
• Experience with document intelligence services (Azure AI Document Intelligence or similar) on real, messy documents.
• Experience with a vector database or search index: embeddings, chunking, hybrid search and relevance tuning.
• Working knowledge of context engineering and token handling.
• Evaluation practice: building golden datasets, running evals in CI, and interpreting results for non-deterministic output.
• OpenTelemetry instrumentation and use of Azure Monitor, Application Insights or equivalent observability tools.

Responsibilities

• Size stories with product owner, flag effort and risks, and confirm data access.
• Test the spec for buildability, prep the repo and agent context, record open questions.
• Slice stories into tasks, estimate in story points, and commit the sprint with the POD.
• Build with coding agents: code, unit/integration tests, and documentation.
• Implement agents on Copilot Studio, Azure AI Foundry Agents or Microsoft Agent Framework, including prompts, tools and workflows.
• Develop data and retrieval layer: document extraction, embedding and vector search.
• Apply context engineering: write/version prompts, manage context windows and token budgets.
• Handle LLM calls with retries, fallbacks, caching and rate limits.
• Build evaluation sets and run evals on every release; fix findings and resubmit.
• Instrument agents with OpenTelemetry; build traces and dashboards for latency and cost.
• Run A/B tests as designed; capture metrics and readouts.
• Deploy through CI/CD, produce release evidence and support handover.

Skills

Full-stack engineering

Python

C#/.NET

API development

LLM/agent apps

Prompt design

RAG workflows

Azure AI Foundry

Copilot Studio

Microsoft Agent Framework

Document Intelligence

Vector databases

Embeddings

Context engineering

Token handling

OpenTelemetry

Azure Monitor

CI/CD

Git workflows

Azure fundamentals

Tools

Azure AI Foundry

Copilot Studio

Microsoft Agent Framework

Azure AI Document Intelligence

Azure AI Search

OpenTelemetry tooling

Azure Monitor

CI/CD pipelines

Job description

Job Title: Full-Stack AI Engineer (Agentic Solutions)

Location: Remote

Duration: Long term contract

Experience:6+ years in software engineering, including 2+ year building LLM or agent solutions

The role You build, evaluate and deploy agentic solutions from an approved spec, using coding agents for most code, tests and documentation. You direct the agents, check their output and own the result. You deliver working software that is instrumented, evaluated, and ready for the business to accept.

What you will do

• Size stories with the product owner, flag effort and risks, and confirm data and access early.
• Test the spec for buildability, prepare the repo and agent context, and record open questions.
• Slice stories into tasks, estimate in story points and commit the sprint with the POD.
• Build with coding agents: code, unit and integration tests, and documentation.
• Implement agents on Copilot Studio, Azure AI Foundry Agents or Microsoft Agent Framework, including prompts, tools, connectors, workflows and integrations.
• Build the data and retrieval layer:
  • Document extraction pipelines with Azure AI Document Intelligence, including validation and confidence handling.
  • Chunking, embedding, indexing and hybrid search in a vector store such as Azure AI Search.
  • Calls to decision and rules APIs, with the LLM handling interpretation and drafting only.
• Apply context engineering: write and version prompts and instructions, manage context windows, memory and tool results, and keep token use within budget.
• Handle LLM calls reliably: structured outputs, retries, fallbacks, caching and rate limits.
• Build evaluation sets and run evals on every release: automated metrics, LLM-as-judge and human review samples. Fix findings and resubmit.
• Instrument every agent with OpenTelemetry. Build traces, dashboards and alerts for latency, token use, cost, errors and quality.
• Run A/B tests as the architect designs them: variant routing, metric capture and result readouts.
• Deploy through CI/CD, compile release evidence for go/no-go, and support the business through validation and handover.

Must have

• Strong full-stack engineering in Python and/or C#/.NET, plus API and integration development.
• Hands‑on delivery of LLM or agent applications: prompt design, function and tool calling, RAG and workflow orchestration.
• Practical experience with at least one of Azure AI Foundry, Copilot Studio or Microsoft Agent Framework.
• Experience with a document intelligence service (Azure AI Document Intelligence or similar) on real, messy documents.
• Experience with a vector database or search index: embeddings, chunking, hybrid search and relevance tuning.
• Working knowledge of context engineering and token handling.
• Evaluation practice: building golden datasets, running evals in CI, and interpreting results for non‑deterministic output.
• OpenTelemetry instrumentation and use of Azure Monitor, Application Insights or an equivalent observability tool to diagnose agent failures.
• Familiarity with A/B testing, feature flags and traffic splitting.
• Daily use of AI coding agents (GitHub Copilot, Claude Code, Cursor or similar). You write clear specs and context files, review agent code critically and catch its mistakes.
• CI/CD, Git workflows, and Azure fundamentals (identity, secrets, networking, monitoring).

Clear communication with business users and daily Agile collaboration.

Microsoft certifications (Azure AI Engineer Associate / Azure AI Apps and Agents Developer Associate)

Nice to have

• Natural-language-to-data solutions and data pipelines (Azure Data Factory, Databricks or Fabric, SQL).
• Rules engines or workflow automation (Power Automate, Logic Apps).
• Healthcare or payer exposure, including PHI handling.