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AI Technology Partners

Enterprise generative AI consulting and implementation

Senior AI Engineer - Agentic Systems

AI Application EngineeringUpdated on Nov 12
Full-timeRemote in USA

About the Job

Requirements

  • Five to eight or more years of software or platform engineering experience, including recent production large language model applications rather than prototypes.
  • Hands-on expertise with one or more agentic frameworks, including LangGraph or LangChain Agents, AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, or Haystack Agents, and tool or function-calling patterns.
  • Strong retrieval-augmented generation engineering across vector databases, chunking and embedding strategies, metadata and search ranking, and grounding techniques.
  • A proven track record building observable, cost-aware, and secure large language model systems, including tracing, evaluations, guardrails, secrets and identity and access management, and personally identifiable information handling.
  • Solid software engineering fundamentals, including Python or TypeScript, asynchronous patterns, APIs, testing, continuous integration and delivery, and containerization.
  • Ability to interface with clients and write concise technical documentation.

Responsibilities

  • Design multi-agent architectures with robust state management, memory, and routing.
  • Choose and implement agent frameworks and justify trade-offs.
  • Build reusable modular components, including planners, tool registries, policy guards, and evaluators.
  • Integrate enterprise tools and data sources using function or tool calling, webhooks, and event-driven flows such as queues, service bus, and functions.
  • Implement retrieval-augmented generation patterns with vector stores and structured knowledge using SQL or graph technologies.
  • Add deterministic fallbacks, circuit breakers, and caching to keep latency and cost predictable.
  • Define service-level indicators and objectives for agent runs; implement tracing, metrics, and logging; and build dashboards for run-level analytics.
  • Create automatic and human-in-the-loop evaluation harnesses to measure groundedness, task success, safety, and cost.
  • Productionize systems with continuous integration and delivery, environment promotion, feature flags, and canary strategies; optimize cost per task and time to success.
  • Enforce content and safety policies using redaction, classification, guardrails, and policy as code; implement role and tenant isolation and data minimization.
  • Collaborate with security teams to align with relevant security and compliance frameworks and deliver audit-ready evidence for agentic workflows.
  • Build privacy-first patterns, including no data exfiltration by default, least-privilege tool access, and secure prompt and trace storage.
  • Work directly with enterprise client teams to translate business processes into agentic designs; present trade-offs and proofs of value that lead to production.
  • Partner with solution leads to create domain-specific agents and reusable templates.

Desired Qualifications

  • Azure-first experience, including Azure OpenAI, Azure AI Studio, Azure Functions, Container Apps or AKS, Private Link or VNet, Key Vault, and Entra ID.
  • Cross-cloud exposure to AWS or GCP, hybrid integrations, and enterprise connectors such as SharePoint or OneDrive, ServiceNow, and Salesforce.
  • Experience with structured output, constrained decoding, JSON Schemas, and program-of-thought planning.

About the Company

AI Technology Partners

Enterprise generative AI consulting and implementation

AI Technology Partners provides consulting and implementation services that help enterprises adopt generative AI technologies, with a focus on strategy and operations. The company guides clients through identifying opportunities, planning deployments, and integrating generative AI tools (such as Microsoft Copilots) into existing workflows to boost growth, productivity, and competitiveness while aiming to reduce costs and manage risks. Its offerings are centered on enterprise-grade advisory and hands-on delivery rather than a stand-alone product. Compared with competitors, the firm emphasizes strategic, operation-level transformation for large organizations and end-to-end support in AI adoption, risk management, and measurable business outcomes. The primary goal is to enable clients to achieve revenue growth, higher employee productivity, and cost savings through a structured AI transformation journey.

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