Lead AI Engineer

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Design and architect systems powered by AI utilizing LLMs, retrieval-augmented generation, agentic workflows, and orchestration patterns.

• Create secure, maintainable, production-ready software platforms and cloud-native services.

• Coordinate models, tools, retrieval systems, and enterprise workflows.

• Develop rapid prototypes and proof-of-concepts to validate technologies and uncover business opportunities.

• Set up evaluation, monitoring, testing, benchmarking, observability, and continuous-improvement practices.

• Lead discussions on technical design and conduct architecture reviews.

• Promote engineering best practices across teams.

• Mentor engineers and cultivate reusable AI capabilities and frameworks.

• Collaborate with product teams, architects, domain experts, customers, and partners.

• Recognize opportunities and deliver tangible business impact.

• Shape IFS’s AI strategy and long-term technological direction through hands-on delivery, experimentation, customer engagement, industry events, and partner collaboration.

⛳️ Requirements

• Bachelor’s degree in computer science, Software Engineering, AI, Data Science, or a related discipline.

• Over 8 years of professional experience in AI, Machine Learning, and/or Software Engineering.

• Demonstrated history of delivering successful projects.

• Experience in transitioning incubated AI solutions to production, including scoping, design, development, testing, deployment, and monitoring.

• Proficient programming skills in one or more mainstream programming languages such as Python, Golang, C#, or TypeScript.

• Familiarity with context engineering, retrieval architecture, embeddings, vector databases, search technologies, and retrieval optimization.

• Solid backend engineering fundamentals, covering APIs, distributed services, cloud-native architectures, CI/CD, integration, automation, and security.

• Background in DevOps and MLOps/LLMOps practices.

• Knowledge of infrastructure-as-code tools like Terraform and package managers such as Helm Charts.

• Capability to design solutions that integrate enterprise applications, business processes, workflows, and data platforms.

• Experience in designing and implementing AI architectures utilizing LLMs, RAG, agentic workflows, orchestration patterns, and enterprise data sources.

• Understanding of the AI system lifecycle, including evaluation, deployment, monitoring, governance, and continuous improvement.

• Experience collaborating with customers, stakeholders, and domain experts to define and deliver solutions.

• Ability to rapidly prototype, experiment, measure outcomes, and iterate in customer and enterprise settings.

• Strong communication skills to convey complex technical concepts to both technical and non-technical audiences.

• Proficiency in translating intricate business problems into technical strategies, execution plans, and measurable outcomes.

• Experience leading technical discussions, influencing architectural direction, mentoring engineers, and achieving alignment across teams.

• Experience with two or more of the specified AI, cloud, infrastructure, model development, or enterprise AI technologies is highly desirable.

• A Master’s degree is a plus, though not required.

🏝️ Benefits

• Flexible and hybrid work arrangements.

• Inclusive workplace culture.

• Opportunity to work in a global, diverse environment.

• Commitment to sustainability.

• Chance to contribute to AI innovation and make a global impact.