Relevantz Technology - Lead AI/ML 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.

- Bachelors 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.