AI Technology Partners

• Design and develop scalable AI learning programs, curriculum, and training materials • Support enablement initiatives across platforms and workflows such as Microsoft Copilot, Claude, ChatGPT Enterprise • Deliver engaging workshops, training sessions, and hands-on enablement experiences • Create learning assets such as prompt libraries, job aids, playbooks, guides, assessments, and LMS-based learning content • Partner with internal teams and enterprise clients to support AI adoption and user enablement efforts • Translate complex AI concepts into practical, accessible learning experiences for both technical and non-technical audiences • Support change management and adoption strategies • Continuously experiment with AI tools and stay current with evolving AI technologies

• Act as a trusted advisor and senior engagement leader across client engagements, driving AI strategy, requirements analysis, and solution architecture. • Partner closely with executive stakeholders to identify high-impact opportunities, design enterprise-grade AI solutions, and guide successful implementation and adoption. • Serve as a senior, client-facing leader and trusted advisor to C-level and senior stakeholders. • Translate business objectives into clear AI strategies, roadmaps, and solution approaches. • Lead executive workshops, discovery sessions, and requirements analysis to define high-value use cases. • Build deep, long-term client relationships grounded in trust, value, and measurable outcomes. • Lead end-to-end solutioning efforts across pre-sales and early delivery phases. • Drive structured requirements analysis, translating business needs into scalable technical architectures. • Design and architect tailored, enterprise-grade AI solutions aligned to client goals, industry context, and constraints. • Partner on proposals, statements of work, and solution positioning. • Lead demos, proofs of concept (PoCs), and technical deep dives to accelerate decision-making. • Identify expansion opportunities and help shape new offerings and go-to-market strategies. • Own the architecture vision across client engagements, ensuring alignment from concept through implementation. • Design enterprise-grade generative AI solutions across cloud platforms. • Build and prototype solutions leveraging tools such as OpenAI, Gemini, Claude, Cohere, Copilot, and emerging frameworks. • Lead architecture across LLM orchestration, RAG pipelines, vector databases, APIs, and AI gateways. • Ensure solutions meet enterprise standards for security, scalability, governance, and compliance. • Provide hands-on technical guidance and architectural oversight to engineering teams. • Act as the engagement lead, ensuring alignment across client stakeholders, delivery teams, and leadership. • Guide delivery teams through implementation while maintaining architectural integrity and business alignment. • Establish high-level governance, milestones, and success metrics. • Support successful operationalization, adoption, and value realization. • Ensure client outcomes are achieved without owning day-to-day delivery execution. • Stay at the forefront of the rapidly evolving AI landscape and bring forward new capabilities. • Contribute to internal IP, frameworks, and repeatable solutions. • Mentor and elevate internal teams on AI strategy, architecture, and delivery best practices. • Represent AITP as a thought leader in client engagements and industry conversations.

About the role AI Technology Partners (AITP) delivers secure, customizable generative AI solutions for enterprises. We need a driver, not a passenger—someone who takes ownership, sets the pace, and keeps delivery on track across multiple client and internal projects. You’ll work hands-on with cross-functional teams, blend Scrum and Kanban, and ensure our AI solutions land on time, in scope, and to our high standards. What you'll do - Lead multiple projects/programs from kickoff to delivery—plan, prioritize, and remove blockers. - Keep teams focused and accountable; turn ambiguity into clear actions and measurable milestones. - Run Agile ceremonies with intent, track velocity, throughput, and scope changes. - Own client communications—set expectations, resolve issues, and maintain trust. - Use AI daily to accelerate PM tasks: summarizing meetings, drafting requirements, updating status, managing risks. - Maintain ruthless attention to detail while keeping the big picture in sight. Qualifications Must-have - Proven track record delivering tech projects in Agile environments (Scrum + Kanban). - Confident, composed leadership of cross-functional teams—able to align strong personalities without ego. - Excellent client management and communication skills. - Strong organizational habits, with the ability to juggle multiple priorities without dropping details. - Working knowledge of generative AI concepts and a habit of using AI tools to work faster and smarter. Nice to have - Background in engineering or DevOps; comfort reading code or infrastructure diagrams. - Experience in regulated environments (ISO 27001, SOC 2, NIST, HIPAA, GDPR). Location Remote, US-based candidates preferred. The role may involve working across multiple time zones. How we work - Driver mindset: You own outcomes and momentum. - Hybrid Agile: Scrum and Kanban blended for speed and adaptability. - AI as leverage: We use AI to deliver more, faster. Compensation - We offer a competitive and flexible compensation package aligned to experience, scope, and engagement model. This may include base salary, performance incentives, and equity participation, designed to reward meaningful contributions and impact. How to Apply Interested candidates are encouraged to submit their resumes and a brief cover letter outlining relevant experience and why they are a good fit for this role. Equal Opportunity Statement AI Technology Partners is committed to equal employment opportunity in all practices and reaffirms that there shall be no unlawful discrimination against any employee or applicant for employment on the grounds of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

• Design multi-agent architectures with robust state management, memory, and routing. • Choose and implement leading frameworks such as LangGraph/LangChain Agents, Microsoft AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, or Haystack Agents—and justify trade-offs. • Build modular components (planners, tool registries, policy guards, evaluators) that are reusable across clients and domains. • Integrate enterprise tools and data sources via function/tool calling, webhooks, and event-driven flows (Queues/Service Bus/Functions). • Implement retrieval-augmented generation (RAG) patterns with vector stores (Azure AI Search, pgvector, MongoDB Atlas, Pinecone, Weaviate, Milvus) and structured knowledge (SQL/Graph). • Add deterministic fallbacks, circuit breakers, and caching to keep latency and cost predictable. • Define SLIs/SLOs for agent runs; implement tracing, metrics, and logging (e.g., Langfuse + OpenTelemetry) and build dashboards for run-level analytics. • Create evaluation harnesses (automatic + human-in-the-loop) using tools such as Ragas, DeepEval, promptfoo to measure groundedness, task success, safety, and cost. • Productionize with CI/CD, environment promotion, feature flags, and canary strategies; optimize cost-per-task and time-to-success. • Enforce content and safety policies (redaction, classification, guardrails) with policy-as-code; implement role/tenant isolation and data minimization. • Collaborate with security teams to align 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 (e.g., RFP assist, incident RCA drafting, knowledge ops) and reusable templates.

• Design multi-agent architectures with robust state management, memory, and routing. • Choose and implement leading frameworks such as LangGraph/LangChain Agents, Microsoft AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, or Haystack Agents—and justify trade-offs. • Build modular components (planners, tool registries, policy guards, evaluators) that are reusable across clients and domains. • Integrate enterprise tools and data sources via function/tool calling, webhooks, and event-driven flows (Queues/Service Bus/Functions). • Implement retrieval-augmented generation (RAG) patterns with vector stores (Azure AI Search, pgvector, MongoDB Atlas, Pinecone, Weaviate, Milvus) and structured knowledge (SQL/Graph). • Add deterministic fallbacks, circuit breakers, and caching to keep latency and cost predictable. • Define SLIs/SLOs for agent runs; implement tracing, metrics, and logging (e.g., Langfuse + OpenTelemetry) and build dashboards for run-level analytics. • Create evaluation harnesses (automatic + human-in-the-loop) using tools such as Ragas, DeepEval, promptfoo to measure groundedness, task success, safety, and cost. • Productionize with CI/CD, environment promotion, feature flags, and canary strategies; optimize cost-per-task and time-to-success. • Enforce content and safety policies (redaction, classification, guardrails) with policy-as-code; implement role/tenant isolation and data minimization. • Collaborate with security teams to align 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 (e.g., RFP assist, incident RCA drafting, knowledge ops) and reusable templates.

• Lead multiple projects/programs from kickoff to delivery—plan, prioritize, and remove blockers. • Keep teams focused and accountable; turn ambiguity into clear actions and measurable milestones. • Run Agile ceremonies with intent, track velocity, throughput, and scope changes. • Own client communications—set expectations, resolve issues, and maintain trust. • Use AI daily to accelerate PM tasks: summarizing meetings, drafting requirements, updating status, managing risks. • Maintain ruthless attention to detail while keeping the big picture in sight.

AI Technology Partners (AITP) is a leader in delivering cutting-edge generative AI solutions and managed services, specializing in secure, customizable AI deployments for enterprises. Our offerings are designed to help organizations unlock the full value of AI while maintaining robust security and compliance across their infrastructures. About the role At AI Technology Partners (AITP), we empower enterprises to scale revenue & profit —with secure, compliant generative AI solutions. In this role, you’ll lead the design and delivery of agentic systems that orchestrate tools, data, and policies to solve real business workflows—safely, reliably, and at scale. If you like greenfield architecture, fast iteration, and measurable impact with enterprise clients, this is your playground. What you'll do Architecture & System Design (Agentic) Design multi-agent architectures with robust state management, memory, and routing. Choose and implement leading frameworks such as LangGraph/LangChain Agents, Microsoft AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, or Haystack Agents—and justify trade-offs. Build modular components (planners, tool registries, policy guards, evaluators) that are reusable across clients and domains. Tooling & Orchestration Integrate enterprise tools and data sources via function/tool calling, webhooks, and event-driven flows (Queues/Service Bus/Functions). Implement retrieval-augmented generation (RAG) patterns with vector stores (Azure AI Search, pgvector, MongoDB Atlas, Pinecone, Weaviate, Milvus) and structured knowledge (SQL/Graph). Add deterministic fallbacks, circuit breakers, and caching to keep latency and cost predictable. Reliability, Observability & MLOps Define SLIs/SLOs for agent runs; implement tracing, metrics, and logging (e.g., Langfuse + OpenTelemetry) and build dashboards for run-level analytics. Create evaluation harnesses (automatic + human-in-the-loop) using tools such as Ragas, DeepEval, promptfoo to measure groundedness, task success, safety, and cost. Productionize with CI/CD, environment promotion, feature flags, and canary strategies; optimize cost-per-task and time-to-success. Safety, Security & Governance Enforce content and safety policies (redaction, classification, guardrails) with policy-as-code; implement role/tenant isolation and data minimization. Collaborate with security teams to align 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). Product & Client Impact 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 (e.g., RFP assist, incident RCA drafting, knowledge ops) and reusable templates. Qualifications Compensation Competitive salary for full-time or hourly rate for contract hire, 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. How to Apply Interested candidates are encouraged to submit their resumes and a brief cover letter outlining relevant experience and why they are a good fit for this role. Equal Opportunity Statement AI Technology Partners is committed to equal employment opportunity in all practices and reaffirms that there shall be no unlawful discrimination against any employee or applicant for employment on the grounds of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.