AI ML Lead Engineer

EDUCATION, EXPERIENCE, & SKILLS REQUIRED

8–11 years of experience in a software engineering role, with a focus on backend or full-stack development

Proven track record of AI/LLM application development or integration

Strong experience in Python-based AI application development with API engineering

Proficiency in RESTful APIs, microservices, and cloud-based AI deployments (AWS, Kubernetes, Lambda)

Familiarity with AI orchestration tools for AI workflow automation

Knowledge of SQL and NoSQL databases (PostgreSQL) for AI-powered search

Experience working in Agile teams and delivering AI-driven features in a cloud-first environment

Bachelor’s Degree in Computer Science or related field

Understanding of healthcare data privacy regulations (HIPAA, GDPR) is a plus

BEHAVIORS & ABILITIES REQUIRED

Ability to learn and adapt rapidly while producing high-quality code

Capable of translating AI/LLM concepts into practical, scalable software solutions

Innovative thinker who finds creative ways to execute when historical context is limited

Strong analytical skills to assess potential designs and choose the best solution for the business

Committed to delivering results under challenging circumstances

Skilled at mentoring and coaching to elevate junior team members

Able to uphold best engineering practices for quality, security, and performance

RESPONSIBILITIES MAY INCLUDE, BUT ARE NOT LIMITED TO

Technical Execution

AI-Powered Software Development & API Integration

Design, develop, and deploy AI-powered applications that enhance RCM automation

Develop AI-driven microservices and ensure cloud-native deployment.

AI Optimization & Performance Tuning

Optimize AI model performance via API configurations rather than custom fine-tuning

Leverage AI orchestration tools (LangChain) to automate complex AI workflows

Microservices & APIs

Build and maintain RESTful APIs for AI features; integrate with internal and external systems

Accurately estimate development tasks and own them through completion

Deliver high-quality software components

Ensure solutions meet reliability, performance, and compliance standards (especially for healthcare data)

Evaluate and propose new technologies

Identify scalable open-source frameworks or cloud-based AI services, ensuring robust and cost-effective implementations

Code reviews & quality assurance

Participate in peer reviews, ensuring adherence to coding conventions and best practices

Write, debug, and deploy code to production, promptly delivering fixes

Contributions to the Team

Subject matter expert

Serve as a go-to resource for AI/LLM-related application architecture and best practices

Stay current with industry trends (agentic AI, genAI) and share insights with the broader team

Scrum team participation

Collaborate in Agile ceremonies: daily stand-ups, sprint planning, retrospectives

Commit to sprint goals and deliver incremental value to customers and internal stakeholders

Team accountability

Encourage a culture of ownership: if you build it, you support it post-release

Help the team continuously improve velocity, code quality, and automation

Cross-Functional Coordination & Communication

Partner with product and UX

Translate requirements for AI-driven RCM features into technical designs, ensuring alignment with user needs

Collaborate on user experience improvements requiring generative AI insights (e.g., claims code suggestions)

Stakeholder engagement

Work closely with compliance/security teams to maintain HIPAA/data governance standards

Communicate technical roadmaps, dependencies, and timelines effectively to non-technical audiences

Broad knowledge sharing

Educate peers on AI/ML design patterns, cloud infrastructures, and best practices

Build strong relationships with cross-functional teams, bridging technology and business domains