Senior Applied AI Scientist, Production-Scale Architect

Lumen

Indianapolis (IN)

On-site

USD 152,000 - 253,000

Full time

4 days ago

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Benefits offered by this job

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Job summary

Lumen is seeking highly technical, product‑minded Senior Lead Applied AI Scientists to design, build, deploy, and improve production‑scale AI solutions across agents, generative AI, and ML workloads. You will partner with business, product, engineering, and technology leaders to translate opportunities into AI‑powered solutions with measurable impact.

The ideal candidate combines deep AI expertise with strong software engineering and product delivery skills, able to prototype, evaluate, and

Qualifications

Seven+ years of experience in applied AI, with production AI deployments.
Proven track record delivering AI solutions that drive measurable business outcomes.
Deep expertise in machine learning, statistics, experimentation, predictive analytics, and modern AI techniques.
Hands‑on experience building LLM, RAG, agentic, and machine learning solutions.
Strong experience with AI evaluation, model performance optimization, responsible AI, and production monitoring.
Proficiency in Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, MLflow, or similar technologies.
Experience with MLOps, LLMOps, cloud AI platforms, APIs, and software engineering best practices.
Strong product mindset, problem‑solving skills, and ability to communicate complex concepts with technical and business stakeholders.

Responsibilities

Design, build, and optimize AI solutions from concept through production deployment.
Partner with business and product teams to identify opportunities, define success metrics, and validate value through rapid experimentation.
Develop advanced AI systems leveraging machine learning, generative AI, retrieval, predictive modeling, and agentic architectures.
Define evaluation frameworks and continuously improve quality, reliability, safety, performance, and cost.
Partner with Engineering to deliver scalable, production‑ready solutions using MLOps and LLMOps best practices.
Contribute reusable frameworks, evaluation assets, and technical standards that accelerate AI adoption across the enterprise.
Provide technical leadership, mentorship, and guidance on complex AI initiatives.