Position Summary:
The AI Engineer designs, develops, and deploys AI/ML-powered software solutions that advance Atlas's business operations and product innovation. Working within the software engineering team, this role builds and integrates AI capabilities-including LLM-based tools, copilots, data pipelines, and cloud applications-in alignment with established architecture, engineering standards, and product roadmaps. The ideal candidate combines hands-on technical depth across the full AI/ML lifecycle with strong collaboration skills, translating requirements from product and engineering leadership into scalable, reliable, production-grade solutions while upholding security, privacy, and responsible-AI practices.
Key Responsibilities:
Solution Development
- Develop, test, and deploy AI-powered software applications, including LLM-based tools, copilots, and automation solutions
- Develop and integrate APIs, services, and data pipelines that support AI functionality
- Contribute to identifying and prototyping high-value AI use cases in partnership with business, engineering, and lab-services stakeholders
- Translate defined requirements from product managers and engineering leadership into working solutions
- Develop reliable, maintainable, and scalable software following team standards and established architectural guidelines
Deployment & MLOps
- Support the deployment and maintenance of AI/ML applications in production environments
- Implement and maintain monitoring, evaluation, and logging mechanisms for AI systems
- Contribute to CI/CD pipelines and model/application lifecycle management
- Support debugging, performance optimization, and system reliability
Collaboration & Process
- Work closely with the software engineering team, product stakeholders, and cross-functional partners
- Collaborate with the Software Engineering Manager and team on system design and implementation approaches
- Participate in sprint planning, code reviews, and agile development processes
- Communicate progress, risks, and technical trade-offs clearly to the Software Engineering Manager and project stakeholders
Compliance & Quality
- Follow established standards for security, privacy, and responsible AI usage
- Support software validation, testing, and documentation per company processes (QMS where applicable)
- Ensure compliance with internal development and deployment policies
- Perform other duties as assigned
Requirements:
Education
- Bachelor's degree in Computer Science, Software Engineering, Data Science, Data Engineering, Electrical/Computer Engineering, or related field required
- Master's degree preferred (AI/ML, Computer Science, Software Engineering, or related)
Experience
- 2+ years in software engineering, architecture, or applied data/ML engineering roles, with experience delivering AI/ML solutions (model development and/or LLM/RAG applications) into production environments
- Hands-on capability designing and building AI-powered applications, including rapid prototyping through production deployment
- Practical experience with the AI/ML lifecycle: data pipelines, evaluation, deployment, monitoring, maintenance, and MLOps
Technical Skills
- Experience with LLM-based applications (prompting patterns, tool/function calling, RAG, embeddings/vector databases, guardrails, and evaluation techniques)
- Experience with cloud platforms (Azure or AWS), APIs/microservices, CI/CD pipelines, and secure deployment practices
- Strong software design and modular development skills; ability to contribute to scalable, maintainable architectures and follow established engineering standards
- Working knowledge of data security, privacy, and responsible AI practices (access control, governance, auditability)
- Familiarity with software verification/validation, risk-based testing, and quality management practices in regulated or quality-managed environments
- Demonstrated ability and willingness to use AI tools to improve productivity, decision-marking, work quality, and to reduce costs. The successful candidate must be able to identify appropriate AI use cases and critically evaluate AI-generated outputs.
Professional Skills
- Able to complete assigned work with appropriate guidance while contributing effectively as a team player in a fast-paced, deadline-driven environment
- Strong interpersonal and communication skills; able to collaborate effectively across engineering and cross-functional teams and contribute to technical documentation and design discussions
- Strong prioritization and organizational skills; able to manage multiple tasks and deliver high-quality results
Preferred / Nice-to-Have
- Relevant certifications: Azure AI Engineer, AWS ML Specialty, Databricks, or equivalent
- Understanding of embedded ML applications
CompensationEmployee Type: Salaried
Currency: USD
Salary Minimum: 120,000
Salary Maximum: 140,000
Incentive: No
Disclaimer: Where a specific pay range is noted, it is a good faith estimate at the time of this posting. The actual salary offered will be based on experience, skills, qualifications, market / business considerations, and geographic location.
For more information on AMETEK's competitive benefits, please click here.
