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Role- AI Engineer (Top Priority)

Client name: JM Family

Location: Deerfield, FL(Only local )

Work Type: Hybrid 3 days onsite per week

Total years: 8-10 years

Key: Along with strong AI engineer need to have below mentioned pointers.

The candidate should possess strong stakeholder management skills.
Excellent communication skills and the ability to articulate ideas effectively are essential.
The individual should be comfortable working in a challenging and fast-paced environment.
The role follows a hybrid work model, and the candidate should be local to the client location.
Building strong rapport with the client is critical; therefore, the candidate is expected to work from the client office on a weekly basis.
The client is looking to have the selected candidate start within the next two weeks.

Write production code. Repeatable work becomes compiled, testable binaries (Go-first); prompts drive persona behavior only. You build the tooling, not slideware about it.

Operate agent fleets. Take a decomposed backlog, fan out parallel streams on conflict-free work, and bring it back through review gates.

Build security in, not on. TDD test-writers ahead of coders, a dedicated validation stage (models hallucinate passing tests), persona judging against threat/security models, failures auto-looped as issues. Signed builds, SBOMs, and access control are table stakes.

Integrate natively. Azure + GitHub Copilot, build-what's-missing in-stack. No third-party platforms, no AWS.

Run model-agnostic. Personas across Claude / Copilot / ChatGPT because they fail differently; disagreement is signal. Manage token and context economics as an engineering constraint - just-in-time context loading, per-task budgets, alerts.

Own your slice end to end. Design, develop, test, integrate, deploy, document, and KT - across the full SDLC.

Must-have

Senior engineer who still ships daily - hands-on-keyboard delivery, no exceptions.

Deep Azure + GitHub Copilot delivery experience (primary stack, not a footnote).

Strong Go (or equivalent systems language) for deterministic, testable orchestration tooling.

Hands-on experience operating multi-agent / multi-model workflows in real delivery, not demos.

Security-native instincts - TDD discipline, secure SDLC, threat modeling; comfort in a vulnerability-response context.

Full-SDLC ownership of a work stream: design through deployment, docs, and knowledge transfer.

Nice-to-have

SIEM / SOAR / EDR, identity, vuln-management, or CMDB / ITSM integration experience.

Eval-harness, red-team, or agent-guardrail work (blast-radius sandboxing, reversibility, confidence thresholds, audit trails).