Lead Software Engineer – AI Agents, Orchestration

Jobtailor; Town of Carmel (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking an experienced AI Platform Architect in New York to own major portions of the AI workload orchestration platform. You will design end-to-end AI frameworks, enabling models, agents and tools to operate together at scale.

You will drive MLOps and LLMOps, implement governance and responsible AI guardrails, and lead cross-team reviews to ensure scalable, reliable developer experience across enterprise teams.

Qualifications

• Bachelor's degree in CS, data engineering, information systems, AI or equivalent.
• 5–7 years of experience in data engineering, AI engineering, or software engineering.
• Strong experience in large-scale data pipelines and distributed processing.
• Experience with Python, SQL, APIs, workflow automation, cloud-native architectures.
• Proven design and deployment of RESTful APIs and web services at scale.
• Excellent communication and collaboration with stakeholders.
• Track record of independently delivering projects from concept to production.
• Strong systems thinking and cross-team influence for scalability and reliability.

Responsibilities

• Own the technical vision and architecture for major portions of the AI platform.
• Design and engineer AI orchestration frameworks coordinating models, agents, tools, APIs, and apps.
• Develop agent-to-agent and human-in-the-loop workflows for complex operations.
• Lead AI context engineering strategies and AI agent architectures.
• Build reusable orchestration patterns for rapid deployment of AI-enabled capabilities.
• Design and develop scalable data pipelines for AI, analytics, and workflows.
• Build enterprise data products optimized for AI consumption.
• Implement MLOps, LLMOps deployment, monitoring, and governance capabilities.
• Establish Responsible AI guardrails, governance, and model risk management processes.
• Develop AI observability, telemetry, and performance measurement solutions.
• Design and implement RAG architectures for products with enterprise teams.
• Lead cross-team architecture reviews and align infrastructure and apps.

Skills

Python

SQL

Data Engineering

Machine Learning Engineering

Workflow Automation

Distributed Data Processing

Systems Thinking

Cross-Team Influence

Project Management

RESTful API Design

Education

Bachelor's degree in Computer Science, Data Engineering, Information Systems, AI or equivalent

Tools

Databricks

Snowflake

Spark

Kafka

Delta Lake

Iceberg

Airflow

FastAPI

React

Azure Cosmos DB

Job description

• Own the technical vision and architecture for major portions of the AI Workload Orchestration Platform
• Design and engineer AI orchestration frameworks coordinating models, agents, tools, APIs, and software applications
• Develop agent-to-agent and human-in-the-loop workflows for complex operational and analytical processes
• Lead AI context engineering strategies and AI agent architectures
• Build reusable orchestration patterns for rapid deployment of AI-enabled business capabilities
• Design and develop scalable data pipelines supporting AI, analytics, and agentic workflows
• Build enterprise data products optimized for AI consumption
• Develop reusable AI platform components for multiple use cases and business domains
• Implement MLOps and LLMOps deployment, monitoring, versioning, and governance capabilities
• Implement Responsible AI guardrails, governance controls, and model risk management processes
• Build AI observability, evaluation, telemetry, and performance measurement solutions
• Design and implement RAG architectures for GSS SW products with Enterprise teams
• Lead cross-team architecture reviews and drive alignment across infrastructure, software application, and Enterprise teams

Requirements

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Artificial Intelligence, or equivalent practical experience
• 5–7 years of experience in Data Engineering, AI Engineering, Machine Learning Engineering, Software Engineering, or related disciplines
• Strong experience developing large-scale data pipelines and distributed data-processing solutions
• Experience with Python, SQL, APIs, workflow automation, and cloud-native architectures
• Proven experience designing, deploying, and maintaining RESTful APIs and web services at scale
• Strong communication and stakeholder collaboration skills
• Track record of independently driving projects from concept through production deployment
• Strong systems thinking, cross-team influence, and long-term view of platform scalability, reliability, and developer experience
• Preferred experience with LangGraph, Semantic Kernel, CrewAI, AutoGen, LangChain, or similar frameworks
• Preferred experience with Databricks, Snowflake, Spark, Kafka, Delta Lake, Iceberg, and Airflow
• Preferred experience with vector databases, semantic search, and enterprise RAG platforms
• Preferred experience implementing MLOps, LLMOps, AI observability, and evaluation frameworks
• Preferred knowledge of Responsible AI, data governance, and model risk management
• Preferred experience with FastAPI, React, and Azure Cosmos DB or similar technology stacks
• Preferred strong understanding of AWS and/or Azure Cloud Platforms

Core Competencies

Demonstrates expertise in designing and implementing AI orchestration frameworks, scalable data pipelines, and MLOps practices. Proficient in developing enterprise data products and ensuring Responsible AI governance and model risk management.

Highest-signal resume keywords

• AI Orchestration Frameworks
• Data Pipeline Development
• MLOps Implementation
• RESTful API Design
• Cloud-Native Architectures

Hard Skills

• Python
• SQL
• Data Engineering
• Machine Learning Engineering
• AI Engineering
• Workflow Automation
• Distributed Data Processing
• Systems Thinking
• Cross-Team Influence
• Project Management

Soft Skills

• Strong Communication
• Stakeholder Collaboration

Industry Keywords

• Responsible AI
• Data Governance
• Model Risk Management
• AI Observability
• Enterprise RAG Platforms

Tools & Technologies

• Databricks
• Snowflake
• Spark
• Kafka
• Delta Lake
• Iceberg
• Airflow
• FastAPI
• React
• Azure Cosmos DB