Lead AI Engineer

IFS

Lead AI Engineer building production LLM, RAG, and agentic solutions for IFS’s enterprise software. Guiding AI architecture, innovation, and engineering teams.

Posted 9/10/2026full-timeRemote • Madrid • Massachusetts • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and architecting AI-powered systems, with a strong focus on LLMs, retrieval-augmented generation, and cloud-native services. Proven ability to lead technical discussions, mentor engineers, and drive engineering best practices while delivering measurable business impact.

Highest-signal resume keywords

AI System DesignMachine Learning ImplementationCloud-Native ArchitectureBackend Engineering FundamentalsDevOps and MLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonGolangC#TypeScriptAPIsDistributed ServicesCI/CDIntegrationAutomationSecurity

Soft Skills

Strong Communication SkillsMentoring EngineersCollaboration with Stakeholders

Tools & Technologies

TerraformHelm ChartsVector DatabasesSearch TechnologiesRetrieval Optimization

Industry Keywords

AIData ScienceSoftware EngineeringEvaluation and MonitoringContinuous Improvement

Tech Stack

Tools & technologies

CloudGoPythonTerraformTypeScript

About the role

Key responsibilities & impact

Design and architect AI-powered systems using LLMs, retrieval-augmented generation, agentic workflows, and orchestration patterns
Develop secure, maintainable, production-ready software platforms and cloud-native services
Orchestrate models, tools, retrieval systems, and enterprise workflows
Build rapid prototypes and proof-of-concepts to validate technologies and identify business opportunities
Establish evaluation, monitoring, testing, benchmarking, observability, and continuous-improvement practices
Lead technical design discussions and architecture reviews
Drive engineering best practices across teams
Mentor engineers and develop reusable AI capabilities and frameworks
Collaborate with product teams, architects, domain experts, customers, and partners
Identify opportunities and deliver measurable business impact
Influence IFS’s AI strategy and long-term technology direction through hands-on delivery, experimentation, customer engagement, industry events, and partner collaboration

Requirements

What you’ll need

Bachelor’s degree in computer science, Software Engineering, AI, Data Science, or a related field
8+ years of professional experience in AI, Machine Learning, and/or Software Engineering
Proven track record of successfully delivered projects
Experience bringing incubated AI solutions to production, including scoping, design, development, testing, deployment, and monitoring
Strong programming skills in one or more mainstream programming languages such as Python, Golang, C# or TypeScript
Experience with context engineering, retrieval architecture, embeddings, vector databases, search technologies, and retrieval optimization
Strong backend engineering fundamentals, including APIs, distributed services, cloud-native architectures, CI/CD, integration, automation, and security
Background in DevOps and MLOps/LLMOps practices
Familiarity with infrastructure-as-code tools such as Terraform and package managers such as Helm Charts
Ability to design solutions integrating enterprise applications, business processes, workflows, and data platforms
Experience designing and implementing AI architectures using LLMs, RAG, agentic workflows, orchestration patterns, and enterprise data sources
Understanding of AI system lifecycle, including evaluation, deployment, monitoring, governance, and continuous improvement
Experience working with customers, stakeholders, and domain experts to define and deliver solutions
Ability to rapidly prototype, experiment, measure outcomes, and iterate in customer and enterprise environments
Strong communication skills for explaining complex technical concepts to technical and non-technical audiences
Ability to translate complex business problems into technical strategies, execution plans, and measurable outcomes
Experience leading technical discussions, influencing architectural direction, mentoring engineers, and driving alignment across teams
Experience with two or more listed AI, cloud, infrastructure, model development, or enterprise AI technologies is highly desirable
Master’s degree is advantageous, not required

Benefits

Comp & perks

Flexible and hybrid work opportunities
Inclusive workplace experiences
Opportunity to work in a global, diverse environment
Commitment to sustainability
Opportunity to contribute to AI innovation and make a worldwide impact