AI and Data Engineering Technical Delivery Lead

About AuxoAI:

AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data.

What We Do

We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions. We help our clients with accelerating their digital and AI journeys through:

· AI Application Development

· Data, Digital and Cloud acceleration using AI

· AI Native Product Engineering

Role Summary:

AuxoAI is seeking an experienced Data & AI Engineering Technical Delivery Lead to lead end-to-end delivery of enterprise AI and Data transformation initiatives. This role combines deep technical expertise in AI engineering, agentic AI, cloud architectures, and data platforms with strong project delivery, client engagement, stakeholder management, and team leadership capabilities.

The ideal candidate has hands-on experience architecting and delivering production-grade Data, AI and agentic applications, with strong expertise in AWS (including Bedrock and AgentCore), Snowflake, and modern agentic AI frameworks and tools such as LangGraph, Knowledge Graphs, LangSmith, and evaluation frameworks. They should have a comprehensive understanding of solution architecture, engineering best practices, CI/CD, security, scalability, performance, and cost optimization.

The role requires end-to-end accountability for technical delivery, from solution design and development through production deployment and ongoing operations. Experience in a consulting or professional services environment, managing enterprise client engagements and leading distributed engineering teams across the US and India, is highly preferred.

Responsibilities:

· End-to-End Delivery: Own the successful delivery of enterprise Data, AI, and Agentic AI projects from solution design through production deployment and ongoing operations.

· Solution Architecture: Lead technical design and architecture decisions, ensuring solutions are scalable, secure, reliable, and cost-effective.

· AI & Agentic Engineering: Guide the development of production-grade AI applications and agents using modern frameworks, orchestration patterns, and engineering best practices.

· AWS Engineering: Provide technical leadership across AWS services, including Bedrock, AgentCore, Lambda, Step Functions, and other cloud-native services.

· Data Engineering: Oversee the design and implementation of data pipelines, ETL/ELT workflows, data models, and integrations across AWS and Snowflake.

· Snowflake Platform: Guide Snowflake architecture, configuration, performance optimization, security, access controls, and cost management.

· Engineering Excellence: Establish and enforce best practices for code quality, version control, CI/CD, automated testing, monitoring, and documentation.

· AI Quality & Reliability: Ensure robust AI evaluation, guardrails, observability, and monitoring to maintain accuracy, reliability, and performance in production.

· Delivery Management: Manage project plans, milestones, resource allocation, dependencies, and deliverables to ensure timely and high-quality execution.

· Risk & Issue Management: Proactively identify technical and delivery risks, resolve bottlenecks, and drive timely mitigation and escalation.

· Client & Stakeholder Management: Serve as the primary technical delivery contact for clients, communicating progress, managing expectations, and building trusted relationships.

· Operational Excellence: Own production readiness, SLAs, operational KPIs, incident management, and continuous improvement of deployed solutions.

· Team Leadership: Lead, mentor, and develop distributed engineering teams across the US and India, driving accountability, collaboration, and technical excellence.

Qualifications:

Required Qualifications:

· Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

· 12+ years in software, data, or AI engineering, including technical leadership and delivery ownership.

· Experience architecting and deploying production-grade AI/ML and agentic applications, including LLMs, RAG, and AI evaluations.

· Hands-on knowledge of LangGraph, LangChain, LangSmith, Knowledge Graphs, and related frameworks.

· Strong expertise in AWS services, including Bedrock, AgentCore, Lambda, Step Functions, and cloud-native architectures.

· Experience with Snowflake, ETL/ELT pipelines, data modeling, dbt, performance tuning, and cost optimization.

· Strong knowledge of Python, APIs, microservices, CI/CD, testing, and production operations.

· Proven experience managing complex enterprise projects, technical teams, delivery risks, and client stakeholders.

· Experience leading distributed engineering teams across onshore and offshore locations.

Preferred Qualifications:

· Experience in technology consulting or professional services delivering enterprise Data and AI projects.

· Experience with Informatica (PowerCenter / IDMC) or similar data integration platforms.

· Relevant AWS, Snowflake, or AI/ML certifications.