
Artificial Intelligence • B2B • Enterprise
AI Technology Partners is a leading provider of generative AI solutions designed to drive business impact and enhance operational efficiencies in enterprises. They offer tailored generative AI services that aim to improve employee productivity, reduce costs, and optimize critical operational processes across various business functions including marketing, sales, and HR. With a focus on practical implementation and comprehensive training, AI Technology Partners ensures clients leverage the power of AI effectively to achieve competitive advantages in their respective markets.
August 13

Artificial Intelligence • B2B • Enterprise
AI Technology Partners is a leading provider of generative AI solutions designed to drive business impact and enhance operational efficiencies in enterprises. They offer tailored generative AI services that aim to improve employee productivity, reduce costs, and optimize critical operational processes across various business functions including marketing, sales, and HR. With a focus on practical implementation and comprehensive training, AI Technology Partners ensures clients leverage the power of AI effectively to achieve competitive advantages in their respective markets.
• This is a remote position. • Senior AI Engineer, Agentic Systems: design multi-agent architectures with robust state management, memory, and routing. • Evaluate frameworks (LangGraph/LangChain Agents, AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, Haystack) and tool-calling patterns. • Build modular components (planners, tool registries, policy guards, evaluators) reusable across clients. • Integrate enterprise tools/data via function/tool calling, webhooks, event-driven flows. • Implement RAG with vector stores (Azure AI Search, pgvector, MongoDB Atlas, Pinecone, Weaviate, Milvus) and structured knowledge. • Add deterministic fallbacks, circuit breakers, caching to reduce latency/cost. • Define SLIs/SLOs; implement tracing, metrics, and logging; dashboards for run-level analytics. • Create evaluation harnesses (Ragas, DeepEval, promptfoo) to measure groundedness, task success, safety, and cost. • CI/CD, environment promotion, feature flags, and canary strategies; optimize cost-per-task and time-to-success. • Enforce content and safety policies; role/tenant isolation and data minimization. • Collaborate with security teams to ISO 27001/SOC 2/NIST/HIPAA/GDPR contexts; deliver audit-ready evidence for agentic workflows. • Build privacy-first patterns (no data exfiltration by default, least-privilege tool access, secure prompt/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.
• 5–8+ years in software/platform engineering with recent production LLM applications (not just prototypes). • Hands-on expertise with agentic frameworks (one or more of: LangGraph/LangChain Agents, AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, Haystack Agents) and tool/function-calling patterns. • Strong RAG engineering across vector DBs, chunking/embedding strategies, metadata/search ranking, and grounding techniques. • Proven track record building observable, cost-aware, and secure LLM systems (tracing, evals, guardrails, secrets/IAM, PII handling). • Solid software engineering fundamentals: Python/TypeScript, async patterns, APIs, testing, CI/CD, containerization. • Clear communicator who can interface with clients and write crisp technical docs. • Azure-first experience (Azure OpenAI, Azure AI Studio, Azure Functions/Container Apps/AKS, Private Link/VNet, Key Vault, Entra ID). • Cross-cloud exposure (AWS/GCP) and hybrid integrations; experience with enterprise connectors (SharePoint/OneDrive, ServiceNow, Salesforce). • Experience with structured output, constrained decoding, JSON Schemas, and program-of-thought planning.
• Ownership & velocity: Small team, big surface area. You’ll design, ship, and iterate quickly. • Security by design: Data governance and safety are table stakes, not afterthoughts. • Evidence over vibes: We measure task success, grounding, and cost—and improve with data. • AI as leverage: We use LLMs to accelerate engineering—not replace it. • Compensation: Competitive salary or hourly rate, commensurate with experience and engagement model. • What we offer: • Challenging work on meaningful, production agentic systems for enterprise clients. • Learning & sharing culture with deep dives, brown bags, and support for certifications/publication. • Inclusive, flexible workplace —bring your whole self; work where you do your best thinking.
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