Overview In this role you will design and deliver production-grade AI systems that blend data, models, retrieval, orchestration, and secure governance. You will shape enterprise AI strategies, define cloud-native architectures across AWS, Azure, and Google Cloud, and drive AI solutions from experimentation to reliable operations. You will lead cross-functional teams and mentor practitioners while advancing responsible AI, security, and governance. This is a chance to influence large-scale AI programs and work closely with clients to create measurable business impact. You will join a human-centered, outcomes-driven consultancy that values collaboration, learning, and practical AI adoption.
Compensation / Benefits- meaningful time off and paid holidays
- parenteral leave
- 401(k) with match
- subsidized health, dental, & vision
- adoption and fertility assistance
- short/long-term disability
Responsibilities- Set technical direction for enterprise-scale AI systems covering data products, model orchestration, agentic workflows, and lifecycle management
- Define secure, scalable cloud-native and hybrid architectures across AWS, Azure, and Google Cloud, including modern AI platform services
- Guide AI strategy and delivery across generative, agentic, multimodal, and knowledge-assisted use cases
- Lead production GenAI and agentic AI adoption with advanced RAG, tool calls, workflow orchestration, and memory management
- Establish AI evaluation, observability, and reliability standards including latency, cost monitoring, and regression testing
- Champion Responsible AI, governance-by-design, explainability, privacy, bias mitigation, and compliance alignment
- Evaluate emerging models and platforms to provide executive-ready recommendations on fit, readiness, cost, and risk
- Lead and mentor cross-functional delivery teams to ensure quality across complex programs
- Drive business development through proposals, client pitches, accelerators, reference architectures, and thought leadership
- Develop senior practitioners and cultivate a culture of continuous learning and responsible AI adoption
- Help hire, mentor, and retain a high-performing, inclusive AI/ML team with clear growth paths
Key requirements- 9+ years in ML/AI solution implementation in production
- 5+ years in professional consulting or IT services with client-facing leadership
- Proven ability to design and govern end-to-end production AI systems
- Deep expertise in GenAI patterns: advanced RAG, embeddings, vector and hybrid search, knowledge graphs, tool invocation
- Experience defining agentic AI architectures with single- and multi-agent workflows
- Proficiency with AI engineering frameworks (e.g., LangChain, LangGraph, LlamaIndex, Semantic Kernel, Haystack, CrewAI, Hugging Face)
- Strong Python programming and modern software practices; APIs, event-driven design, IaC, scalable services
- Experience with cloud AI/ML platforms (Bedrock, SageMaker, Azure AI Foundry/ML, Vertex AI) and hosting/evaluation capabilities
- Experience with enterprise data ecosystems (Databricks, Snowflake, Spark, Kafka, dbt, vector databases, lakehouse, data governance)
- Experience setting MLOps/LLMOps standards (CI/CD, model/prompt versioning, automated evaluation, observability, Kubernetes, serverless, cost/perf)
- Strong ability to communicate complex AI concepts to diverse stakeholders, translating into business value and governance needs
- Experience managing senior delivery teams and shaping AI/ML roadmaps and adoption plans
- Strong problem-solving, critical thinking, and business acumen
- leadership and mentoring
- clear communication
- stakeholder management
- LangChain
- LangGraph
- LlamaIndex
