Scan your resume against ATS criteria for this Lead AI Engineer role at IFS.
As a Lead AI Engineer, you will design and build applied AI solutions that drive measurable business value from concept through scalable production deployment. You'll architect enterprise AI systems leveraging large language models, retrieval-augmented generation, and agentic workflows while leading technical strategy and mentoring engineering teams.
Bachelor’s degree in computer science, Software Engineering, AI, Data Science, or a related field. Master's degree is advantageous.
8+ years of professional experience in AI, Machine Learning, and/or Software Engineering, backed by a proven track record of successfully delivered projects.
Experience bringing incubated AI solutions to production, including scoping, design, development, testing, deployment, and vigilant monitoring.
Strong programming skills or more mainstream programming languages such as Python, Golang, C# or TypeScript.
Experience with context engineering, including retrieval architecture, embeddings, vector databases, search technologies, and retrieval optimization techniques.
Strong backend engineering fundamentals, including APIs, distributed services, cloud-native architectures, CI/CD, integration, automation, and security.
A solid background in DevOps and MLOps/LLMOps practices, and familiarity with tools to manage infrastructure as code, like Terraform and package managers like Helm Charts.
Ability to design solutions that integrate enterprise applications, business processes, workflows, and data platforms.
Experience designing and implementing AI-driven architectures using LLMs, retrieval-augmented generation (RAG), agentic workflows, orchestration patterns, and enterprise data sources.
Strong understanding of the AI system lifecycle, including evaluation, deployment, monitoring, governance, and continuous improvement.
Experience with MLOps lifecycles, deployment pipelines, model operations, and observability for AI systems is advantageous.
Experience working closely with customers, stakeholders, and domain experts to define and deliver solutions.
Demonstrated ability to rapidly prototype, experiment, measure outcomes, and iterate quickly in real-world customer and enterprise environments.
Strong communication skills, with the ability to explain complex technical concepts clearly to technical and non-technical audiences.
Comfortable operating in ambiguous, fast-moving environments, translating complex business problems into clear technical strategies, execution plans, and measurable outcomes.
Experience leading technical discussions, influencing architectural direction, mentoring engineers, and driving alignment across teams.
Track record of influencing technical direction and technology strategy through hands-on delivery, experimentation, and evidence-based recommendations.
LLM Serving & AI Platforms
vLLM, LiteLLM, KServe or similar LLM serving platforms.
AI gateways, model routing, inference serving and multi-modal orchestration.
Foundation Model
Cohere, OpenAI, Anthrophic, Llama, Mistral, DeepSeek or other open-source LLMs.
Agentic AI
LangGraph, PydanticAI, Semantic Kernel, CrewAI, AutoGen or similar agentic AI frameworks.
Tool calling, MCP, workflow orchestration and autonomous agents.
AI Evaluation & Observability
MLFlow, DeepEval, Ragas, Promptfoo, Langfuse or similar evaluation and observability tools.
Cloud & Infrastructure
Kubernetes, Docker, Helm, Terraform and cloud-native deployments platforms.
GPU infrastructure and inference optimization.
Model Development
Hugging Face ecosystem (Transformers, PEFT, LoRA).
Fine-tuning, model evaluation, benchmarking, prompt engineering and model optimization.
Experience building enterprise AI platforms or developer tooling.
Experience working with AMD, NVIDIA, or other AI accelerator technologies.
Experience with enterprise software domains such as ERP, EAM, Service Management, Manufacturing, Supply Chain, or Field Service.
Experience building customer-facing demonstrations, proof-of-concepts, or innovation showcases.
Contributions to open-source AI projects, technical communities, conferences, or publications.
Experience working with Microsoft Azure, AWS, or Google Cloud AI services.
Experience building enterprise AI platforms or developer tooling.
Experience working with AMD, NVIDIA, or other AI accelerator technologies.
Experience with enterprise software domains such as ERP, EAM, Service Management, Manufacturing, Supply Chain, or Field Service.
Experience building customer-facing demonstrations, proof-of-concepts, or innovation showcases.
Contributions to open-source AI projects, technical communities, conferences, or publications.
Experience working with Microsoft Azure, AWS, or Google Cloud AI services.
We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.
How to apply for Lead AI Engineer at IFS?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
8+ years of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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