Engineer Senior

Elevance Health•Indianapolis, IN

9d•Hybrid

About The Position

The Engineer Senior delivers end-to-end application and system development and maintenance across complex, multi-technology platforms for an assigned client group, business unit, or corporate department. The role researches, evaluates, and proposes emerging technologies, including Generative AI, LLM applications, automation frameworks, AI engineering practices, and applied machine learning. It designs, develops, and supports scalable applications and helps identify practical AI use cases that improve business processes, customer experiences, engineering productivity, and operational efficiency. The position supports the design and integration of AI-enabled applications such as chatbots, copilots, document-processing solutions, knowledge search, workflow automation, and decision-support tools. It assesses data, systems, and business processes for opportunities to use structured and unstructured data in Generative AI, analytics, automation, and machine learning. The Engineer Senior works with customers and stakeholders to establish requirements, owns the change-request process, contributes technical advice to cross-functional decisions, and prepares application scope, objectives, and technical or functional specifications. The role may own technical testing and ensure implementation follows the plan, maintains the technical development environment, and performs design and code reviews. It provides technical guidance and mentoring, may lead multiple small to medium-sized projects, and begins setting direction at the project or service level. The position is hybrid and requires associates to work in-office one to two days per week; candidates generally must live within reasonable commuting distance of an office unless an accommodation is granted as required by law.

Requirements

Bachelor's degree in Information Technology, Computer Science, or a related field, and at least 5 years of related experience; equivalent education and experience may qualify.
Multi-dimensional platform experience.
Expert-level experience with business and technical applications, or an equivalent combination of education and experience.

Nice To Haves

Strong engineering experience with hands-on experience or a deep interest in AI engineering, Generative AI, LLM applications, automation, and applied machine learning.
Experience designing, building, or integrating AI-enabled applications, such as chatbots, copilots, intelligent search, document processing, recommendation systems, workflow automation, or decision-support solutions.
Familiarity with LLM concepts such as prompt engineering, retrieval-augmented generation, embeddings, vector databases, model evaluation, responsible AI, guardrails, and production monitoring.
Experience with modern software engineering practices, APIs, cloud platforms, data pipelines, and scalable application architecture.
Experience evaluating or integrating AI platforms, Generative AI tools, automation technologies, or cloud-based AI services.
Multi-database and/or multi-language experience.
Experience mentoring others, leading multiple small projects, and providing troubleshooting support.

Responsibilities

Research, evaluate, and propose technologies, including Generative AI, LLM applications, automation frameworks, AI engineering practices, and applied machine learning solutions.
Design, develop, and support scalable applications, including AI-enabled capabilities and integrations with emerging technologies where appropriate.
Identify, evaluate, and help implement practical Generative AI use cases that improve business processes, customer experiences, engineering productivity, and operational efficiency.
Support the design and integration of AI-enabled applications such as chatbots, copilots, document processing, knowledge search, workflow automation, and decision-support tools.
Assess data, systems, and business processes to identify opportunities to use structured and unstructured data for Generative AI, analytics, automation, and applied machine learning.
Provide technical guidance and mentoring on engineering practices, AI-enabled development patterns, automation, LLM application design, and applied machine learning concepts.
Balance technical, analytical, AI, security, compliance, and product needs when developing technical solutions.
Conduct technical design reviews and code reviews, including reviews of AI-enabled solutions for scalability, maintainability, security, quality, observability, and responsible implementation.
Support vendor evaluation of AI platforms, LLM tools, automation technologies, cloud services, and software engineering solutions.
Maintain active relationships with customers and stakeholders, determine business requirements, and lead requirements-gathering meetings.
Own the change-request process and coordinate with other teams as necessary.
Provide technical advice and contribute to technical decisions affecting cross-functional teams.
Develop and define application scope and objectives and prepare technical and/or functional specifications.
May own technical testing, ensuring unit testing meets test plan requirements, system testing is completed, and implementation follows the plan.
Maintain the technical development environment.
Mentor others and potentially lead multiple small to medium-sized projects.
Begin setting direction at the project or service level and influence decision-making.
Identify and propose strategies for technical problems affecting the team, communicate standards, and gain buy-in on solutions.
Facilitate group sessions for requirements clarification, solution design, AI use case evaluation, code reviews, and troubleshooting.