Scale Ai Data Labeling Jobs (Flexible Options) in Indiana

Overview

Our AI Technical Lead is responsible for designing and delivering scalable AI systems that enable intelligent applications across the organization. This role combines hands‑on engineering, system architecture, and technical leadership to build production‑grade machine learning and generative AI platforms. The Lead works closely with product, data engineering, and infrastructure teams to bring AI capabilities from experimentation into reliable production systems while supporting the organization’s broader AI strategy and innovation initiatives.

Location: Preferred hybrid work location (onsite and WFH). There may be an opportunity for fully remote within a mutually acceptable location.

Key Responsibilities

• Technical Leadership – Provide technical leadership and mentorship to a team of AI engineers. Establish engineering standards, coding practices, and architectural guidelines for AI system development. Lead design reviews, guide technical decision making, and resolve complex engineering challenges. Serve as a technical escalation point for AI system architecture and implementation.
• AI System Architecture – Architect end‑to‑end AI systems including data pipelines, model training workflows, AI service layers, and scalable AI application infrastructure. Design and implement AI‑powered applications including large language model (LLM) systems and retrieval‑based knowledge applications. Define architecture patterns that support experimentation, rapid prototyping, and production deployment of AI capabilities. Develop service‑based architectures that enable AI functionality to be integrated across enterprise applications.
• AI Engineering & Development – Develop and deploy machine learning and generative AI solutions that support enterprise use cases. Build reusable AI services and platform components that enable teams to rapidly develop and scale AI capabilities. Implement evaluation, monitoring, and reliability systems to ensure consistent model performance. Optimize AI pipelines for performance, scalability, and operational efficiency.
• Cloud & MLOps – Design cloud‑native infrastructure supporting AI and machine learning workloads. Implement containerized AI services and automated deployment pipelines. Support the development of scalable AI platforms that enable experimentation, model deployment, and operational monitoring. Ensure AI systems follow best practices for reliability, observability, and cost management.
• Collaboration & Delivery – Work closely with product managers, data engineers, and business stakeholders to identify and deliver high‑value AI use cases. Translate business requirements into scalable AI architecture and engineering solutions. Partner with cross‑functional teams to move AI solutions from pilots and experimentation into production environments. Support initiatives that enable the organization to scale AI capabilities across multiple business domains.
• Responsible AI & Governance – Promote responsible AI practices including transparency, fairness, and privacy considerations. Implement safeguards and monitoring systems for AI applications operating in production. Collaborate with security and compliance teams to ensure AI systems meet regulatory and organizational standards.

Required Education

• Bachelor or International Equivalency degree in Cybersecurity, Computer Science, Electrical Engineering, Information Systems, or closely related field of study; or equivalent work experience (Two years’ relevant work experience is equivalent to one-year college).
• Associate Degree in Computer Science, Electrical Engineering, Information Systems, or closely related field of study + 2 years additional experience.

Required Experience

• 6+ years of experience in software engineering, machine learning engineering, and/or related AI/ML technical roles.
• Experience designing and deploying machine learning or generative AI systems.
• Strong programming experience in Python and modern backend technologies.
• Experience building distributed systems or cloud‑native architectures.
• Experience implementing machine learning workflows or model deployment pipelines.
• Preference for additional experience in developing LLM applications, retrieval‑based AI systems or knowledge‑driven applications, working with cloud platforms and modern DevOps practices, mentoring engineers, leading technical initiatives, and working with large‑scale data pipelines.

Compensation

A good faith estimate of the current pay range is $118,506 – $177,758. The position is eligible for an annual incentive bonus. Compensation decisions depend on competencies, education, qualifications, certifications, experience, skills, seniority, performance, travel requirements, internal equity, business or organizational needs, and alignment with market data. The company typically does not hire at the top of the range.

Benefits

We offer a robust package of benefits including paid time off, paid holidays, community service and self‑care days, medical/dental/vision/pharmacy insurance, 401(k) matching and a non‑contributory plan, life insurance, short and long‑term disability, education reimbursement, employee assistance plan (EAP), adoption assistance program and paid family leave program. We will adhere to all relevant state and local laws concerning employee leave benefits, in line with our plans and policies.

EEO Statement

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. Blue Cross of Idaho is committed to providing reasonable accommodations to qualified individuals with disabilities who are otherwise not able to fully use electronic and online job application systems.

Reasonable Accommodations

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed above are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.