AI Architect

Anblicks Inc.; Addison (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Anblicks Inc. seeks a senior technical leader to own platform architecture and drive production-ready solutions. You will build and ship core components, guiding a team through complex, data-sensitive deployments.

You will align with enterprise clients on architecture narratives, implement scalable multi-tenant patterns, and specialize in LLM-enabled applications with leading cloud AI stacks.

Qualifications

• 10+ years building and operating production distributed systems.
• 3+ years shipping LLM-based systems.
• Experience with major cloud AI stacks and tradeoffs such as AWS Bedrock, Azure AI Foundry, or equivalents.

Responsibilities

• Own architecture decisions and reference architecture for the platform; drive review with enterprise architects at Fortune 500 clients.
• Build production code; this role is roughly 70% hands-on — you set direction by shipping the hard parts.
• Define the evaluation strategy: offline eval harnesses, regression suites for non-deterministic systems, and the quality bar that gates promotion.
• Design multi-tenant isolation, identity, and authorization patterns (OIDC/PKCE, M2M, JIT provisioning) suitable for data-sensitive clients.
• App Development: Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama).
• Model and control unit economics — per-session token cost, agentic loop multipliers, model tiering — so engagements stay margin-positive.
• Mentor senior and lead engineers; raise the ceiling of the org, not just the output of a project.
• Partner with go-to-market on technical positioning, competitive differentiation, and executive-level architecture narratives.

Skills

Distributed systems

LLM systems

Cloud AI stacks

Server-side languages

IaC

Job description

• Own architecture decision records and reference architecture for the platform; drive review with enterprise architecture teams at Fortune 500 clients.
• Build production code. This role is roughly 70% hands-on — you set direction by shipping the hard parts,
• Define the evaluation strategy: offline eval harnesses, regression suites for non-deterministic systems, and the quality bar that gates promotion.
• Design multi-tenant isolation, identity, and authorization patterns (OIDC/PKCE, M2M, JIT provisioning) suitable for data-sensitive clients.
• App Development: Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama).
• Model and control unit economics — per-session token cost, agentic loop multipliers, model tiering — so engagements stay margin-positive.
• Mentor senior and lead engineers; raise the ceiling of the org, not just the output of a project.
• Partner with go-to-market on technical positioning, competitive differentiation, and executive-level architecture narratives.

Required Qualifications

• 10+ years building and operating production distributed systems; 3+ years shipping LLM-based systems.
• Deep experience with at least one major cloud AI stack (AWS Bedrock / AgentCore, Azure AI Foundry, or equivalent) and fluency in the tradeoffs of the others.
• Strong grounding in one server-side language at production depth (Java/Spring Boot, Python, TypeScript) plus infrastructure-as-code.
• Practical experience with agentic patterns: tool use, multi-step planning, orchestration, human-in-the-loop approval flows, MCP or comparable protocol work.
• Track record designing for compliance-sensitive environments — audit logging, data residency, least-privilege authorization, policy enforcement.
• Ability to hold a technical argument with a client's chief architect and a business argument with their CFO in the same meeting.

Preferred

• Prior work on compilers, type systems, policy engines, or CI/CD platforms — the mental model transfers directly.
• Consulting or professional services background; comfort with multi-client context switching.
• Experience with Snowflake, databricks or data governance tooling, or enterprise data quality platforms.