Lead Applied AI Engineer

Lead Applied AI Engineer

Job Title: Lead Applied AI Engineer

Location: New York, NY / Louisville, KY

Duration: 6 months

Preferred Work Location: 1700 Broadway, Suite 3400, New York, NY 10019 Louisville, KY

Experience Required: 8–10 years

Primary Skill Category: AI and Automation

Role Summary

Architect, build, deploy, and scale advanced enterprise AI solutions.

Integrate: Generative AI, AI agents, Modern enterprise platforms

Deliver production-grade AI systems supporting large-scale business operations.

Ensure high standards for Security, Reliability, Governance, Responsible AI, Scalability

Define enterprise AI engineering standards and best practices.

Lead enterprise AI adoption.

Mentor engineering teams.

Work across AI innovation, Enterprise architecture, Platform engineering, Responsible AI governance

AI Solution Architecture

Architect end-to-end AI systems, including Advanced RAG pipelines, Multi-stage retrieval and re-ranking, Agent orchestration frameworks, Multi-agent architectures, Multi-model AI integrations

Design modular, extensible, scalable, and operationally efficient solutions.

Build architectures that can adapt to evolving business requirements.

AI Engineering Standards & Optimization

Define enterprise standards for Prompt engineering, Prompt templates, Prompt versioning, Testing methodologies, AI evaluation frameworks

Establish optimization strategies for Model selection, Caching, Resource utilization, Cost optimization, Performance

Production Deployment & Reliability

Lead production deployment of AI solutions.

Implement Observability, Logging, Distributed tracing, Reliability engineering, Graceful degradation, Circuit breakers, Real-time monitoring dashboards, Automated alerting, Incident response procedures

Ensure AI services meet enterprise SLOs and reliability requirements.

Data & Retrieval Architecture

Design scalable data ingestion frameworks for Structured data, Unstructured documents, Real-time event streams

Develop Vector database architectures, Hybrid search, Data preprocessing pipelines, Data quality monitoring

Implement data cleansing, enrichment, and governance processes.

Ensure high-quality data inputs for AI systems.

AI Evaluation & Continuous Improvement

Establish quantitative AI evaluation frameworks.

Implement A/B testing, Performance benchmarking, User feedback analysis, Telemetry-based optimization

Continuously improve Prompts, Retrieval strategies, Agent workflows, Model configurations

Platform & Infrastructure Collaboration

Partner with platform and infrastructure teams to support AI workloads.

Define requirements for GPU infrastructure, Model-serving platforms, Feature stores, Scalable data storage, Networking infrastructure

Define enterprise AI platform capabilities and integration patterns.

Technical Leadership & Mentoring

Mentor engineers through Architecture reviews, Design guidance, Code reviews, Career development

Promote engineering excellence through Best-practice documentation, Technical training, Communities of practice

Foster responsible and ethical AI development.

Responsible AI & Compliance

Ensure AI solutions comply with enterprise governance and regulatory requirements.

Document System behavior, Decision logic, Evaluation methodologies

Apply responsible AI principles, including Fairness, Transparency, Accountability, Bias mitigation

Support compliance with applicable regulatory and industry standards.

Required Qualifications

7+ years of software engineering experience with strong AI/ML focus.

Proven experience building and operating distributed systems at scale.

Demonstrated success delivering AI-driven business outcomes.

Experience leading large and complex technical initiatives.

Bachelor's degree in Computer Science, Engineering, Data Science, Related discipline

Equivalent practical experience may be considered.

Generative AI Expertise

Deep experience designing and deploying production-grade Generative AI solutions.

Strong experience with Advanced RAG architectures, Multi-hop retrieval, Reasoning systems, Agent orchestration, Tool-using AI agents, Memory-enabled AI systems, Multi-model AI architectures, Conversational AI platforms

Enterprise Solution Delivery

Lead complex AI initiatives across multiple cross-functional teams.

Translate business objectives into Technical solutions, AI architectures, Delivery roadmaps

Drive AI initiatives from Concept, Architecture, Development, Production deployment, Optimization

Technical Skills

Python, FastAPI, React, Distributed systems, Vector databases, Embedding models, LLM APIs, Agent orchestration frameworks, Cloud-native architectures, AI platform engineering, Production AI deployment

AI Engineering Best Practices

Establish enterprise standards for Prompt engineering, Version control, Testing, AI evaluation, Model observability, Cost tracking, Performance tracking, Benchmarking, Data-driven optimization

Responsible AI & Governance

Strong understanding of Responsible AI, Model governance, Risk management, Model validation, Change management, Production monitoring, Deployment practices in regulated environments

Preferred Qualifications

Technical leadership across organizational boundaries.

Strong mentoring and coaching skills.

Ability to collaborate with Product Management, Data Science, Engineering, Security, Compliance, Architecture, Business stakeholders

Experience in regulated industries preferred, including Healthcare, Life Sciences, Insurance

Primary Skills for TAG Search

Must Have

• Generative AI
• Agentic AI
• RAG Architecture
• AI Agents
• Multi-Agent Systems
• Python
• FastAPI
• Vector Databases
• LLM Integration
• AI Platform Engineering
• Production AI Deployment
• AI Evaluation Frameworks
• Prompt Engineering
• Observability & Monitoring
• Enterprise Architecture

Strongly Preferred

• React
• Cloud AI Platforms
• Azure
• OpenAI / Azure OpenAI
• Healthcare Domain Experience
• Responsible AI
• AI Governance
• Distributed Systems Engineering

Keywords

• AI Engineer
• Applied AI Engineer
• Lead AI Engineer
• Generative AI
• Agentic AI
• AI Agents
• RAG
• LLM
• LLM Integration
• Multi-Agent Systems
• Python
• FastAPI
• React
• Vector Database
• AI Platform
• AI Architecture
• AI Evaluation
• Prompt Engineering
• AI Governance
• Responsible AI
• Cloud AI
• Azure OpenAI
• Distributed Systems
• AI and Automation