Sr Artificial Intelligence Technical Lead

Ranger Technical Resources; Town of Florida (NY); On-site; USD 180,000 - 280,000; Full time

Job summary

Ranger Technical Resources partner company is a growing SaaS technology firm serving legal and accounting professionals with secure, customer‑facing software and a live AI platform. They seek a Senior AI Tech Lead who wants meaningful ownership while remaining hands‑on, to shape architecture and write production software.

You will guide engineers and establish standards across AI agents, retrieval pipelines, data integrations, distributed services, and AWS infrastructure, including Bedrock, to

Qualifications

• Bachelor’s degree or equivalent professional experience in CS/SE or related field.
• 10+ years as hands-on software engineer leading complex systems.
• Experience moving an AI platform from MVP to scalable production.
• Hands-on AI design in AWS, Bedrock, and AWS AI ecosystem.
• Advanced Python for production-grade apps.
• Experience with distributed SaaS, data-access patterns, handling sensitive data.
• Proven use of AI-assisted development to boost productivity while enforcing standards.

Responsibilities

• Learn the existing AI platform and assume long-term technical ownership.
• Evolve platform into scalable, secure, reliable foundation for customer AI products.
• Write production Python code and stay involved in development and deployment.
• Lead platform‑level architecture decisions and communicate tradeoffs.
• Design agentic systems: orchestration, tool interaction, routing, and inter-agent communication.
• Build data-access patterns connecting AI with SaaS apps and customer data.
• Establish AI evaluation, regression testing, guardrails, and observability practices.
• Improve performance, reliability, scalability, latency, and operating cost.
• Design security, access control, governance, and data protection for sensitive info.
• Strengthen citation and source-attribution for AI responses.
• Review architecture and production code for quality and risk.
• Set practical engineering standards for deploying AI systems.
• Mentor senior engineers and influence technical direction without formal management.

Skills

AWS AI Ecosystem

Amazon Bedrock

Python

Agentic AI Systems

Distributed Systems

LLMOps

AI Evaluation

AI Observability

AI Guardrails

AI Regression Testing

Retrieval‑Augmented Generation

Vector Databases

Knowledge Graphs

Data Security

System Reliability

Technical Leadership

Education

Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent professional experience

Job description

Our partner is a growing SaaS technology company serving legal and accounting professionals through secure, customer-facing software and a live AI platform. The next challenge is scaling that foundation to support multiple AI products and increasingly complex customer needs.

This is an opportunity for a Senior AI Tech Lead who wants meaningful ownership while remaining hands‑on. You’ll shape the architecture, write production software, guide engineers, and establish standards across AI agents, retrieval pipelines, data integrations, distributed services, and AWS infrastructure. Success requires thinking beyond individual AI features and understanding how to build a secure, reliable, and maintainable enterprise AI platform.

Experience and Education:

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent professional experience.
• 10+ years of hands‑on software engineering experience writing and reviewing production code while architecting complex systems and leading technical decisions.
• Proven background taking an existing AI platform from MVP or early production into a scalable, secure, and reliable customer‑facing environment.
• Deep hands‑on experience designing production AI solutions within AWS, including Amazon Bedrock and the broader AWS AI ecosystem.
• Advanced Python experience building, testing, deploying, and supporting production applications.
• Experience designing distributed SaaS platforms, enterprise integrations, data‑access patterns, and systems involving sensitive customer information.
• Demonstrated experience using AI‑assisted development to improve engineering productivity while maintaining rigorous software engineering standards.

Skills and Strengths:

• AWS AI Ecosystem
• Amazon Bedrock
• Python
• Agentic AI Systems
• Distributed Systems
• LLMOps
• AI Evaluation
• AI Observability
• AI Guardrails
• AI Regression Testing
• Retrieval‑Augmented Generation
• Vector Databases
• Knowledge Graphs
• Data Security
• System Reliability
• Technical Leadership

Primary Job Responsibilities:

• Learn the existing AI platform from the AWS consulting team and progressively assume long‑term technical ownership.
• Evolve the current platform into a scalable, secure, reliable, and production-ready foundation for customer‑facing AI products.
• Write production Python code and remain actively involved in development, testing, deployment, and troubleshooting.
• Lead platform‑level architecture decisions and clearly communicate the tradeoffs behind them.
• Design agentic systems, including agent orchestration, tool interaction, model routing, and communication between specialized agents.
• Build retrieval and data‑access patterns connecting AI capabilities with SaaS applications, enterprise services, and customer information.
• Establish AI evaluation, regression‑testing, guardrail, observability, and monitoring practices.
• Improve platform performance, reliability, scalability, latency, and operating cost as customer adoption grows.
• Design security, access‑control, governance, and data‑protection capabilities for sensitive legal and customer information.
• Strengthen citation and source‑attribution capabilities for AI‑generated responses.
• Review architecture and production code for quality, security, maintainability, and operational risk.
• Establish practical engineering standards for deploying and operating production AI systems.
• Mentor senior engineers and influence technical direction without relying on formal management authority.