Deep experience designing and deploying production-grade Generative AI solutions. Deliver production-grade AI systems supporting large-scale business operations.
Numbers & Facts
Location
New York, NY
Salary
$64.39–$68.18 Per Hour
Description
Job Details
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: