Staff AI Engineer

Bluefish; Germany (OH); On-site; USD 180,000 - 240,000; Full time

Job summary

Bluefish seeks a Staff AI Engineer to lead architectural decisions for LLM-powered products in marketing tech. You will own data platforms end-to-end, balance performance and cost, and mentor engineers across teams.

The role emphasizes translating business goals into data products, setting quality bars, and shipping experiments to production while maintaining security and reliability.

Qualifications

• 8+ years building and operating production data systems.
• Experience deploying LLMs in real-world scale.
• Strong Python and modern service architecture skills.
• Proficient in data modeling and feature engineering.
• Proven cross-functional leadership and mentorship.

Responsibilities

• Lead end-to-end architecture for data platforms and pipelines, balancing performance, reliability, security, and cost.
• Incrementally scale pipelines with safe rollout plans and data quality metrics.
• Translate business goals into actionable data products and draft clear RFCs.
• Establish engineering standards, testing strategies, observability, and data contracts.
• Mentor senior engineers and drive collaboration across software, devops, product, and design.
• Operate with startup agility, embracing ambiguity and driving reliability.
• Define how AI engineers work with cross-functional teams to deliver impactful solutions.
• Prototype data/ML capabilities and evaluate ROI for productionization.

Skills

Python

System design

LLM deployment

Data modeling

Cross-team leadership

Tools

Terraform

CI/CD pipelines

Cloud platforms (AWS/GCP/Azure)

Job description

About The Position

As a Staff AI Engineer, you’ll serve as a technical leader for our LLM‑powered products at the forefront of marketing and advertising technologies. You’ll own critical architectural decisions, set quality bars, and lead multi‑team initiatives that drive measurable outcomes.

What You’ll Be Doing

• Lead end‑to‑end architecture for data platforms and pipelines: scraping, data extraction, transformation, storage, serving, and ML/LLM integration, balancing performance, reliability, security, and cost.
• Incrementally scale pipelines and systems: design safe rollout plans and north‑star data‑quality metrics to handle customer and traffic growth without impacting production.
• Translate business goals into actionable data products: assess high‑level requirements, carve clear problem spaces, draft crisp RFCs, and sequence work into deliverable projects for the team.
• Establish and enforce engineering standards: testing strategy, evals, observability, data contracts, and security practices across services. Think through short‑term and long‑term goals to come up with fast go‑to‑market products, while planning ahead for productization.
• Up‑level the org: lead architecture reviews, codify patterns, mentor senior engineers, and multiply impact through documentation, code reviews, and pairing.
• Startup‑ready: flexible, comfortable with ambiguity and constant change; proactive about process, documentation, and reliability without over‑engineering.
• Lead the collaboration and define how AI engineers work cross‑functionally with software engineers, devops, product managers and designers, to conceptualize and shape innovative and impactful solutions. Provide mentorship to junior team members and cultivate a culture of collaboration and innovation.
• Ship meaningful experiments: prototype data/ML capabilities, evaluate feasibility and ROI, and make pragmatic calls on productionalizing with an eye on operating costs and risk.

Qualifications

• 8+ years building and operating production data systems, including leading cross‑cutting architectural changes, and deploying LLMs in real‑world scenarios at scale.
• Deep experience with Python and modern service architectures; strong system design and data modeling fundamentals.
• Extensive experience with training and deploying machine learning models, particularly within the NLP/LLM domain. Proficiency in Python. Familiarity with infrastructure as code, CI/CD, and cloud infrastructure.
• Fluency in operational maturity: SLOs, on‑call/incident practices, and observability.
• Strong analytical and problem‑solving abilities, with a bias towards action and outcomes. Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Demonstrated leadership experience, with the ability to guide and inspire a team.

About Bluefish

Bluefish believes that AI represents the next major chapter of the internet – and that consumers will increasingly use AI to consume information and media online. On this new AI internet, brands will need new tools and technologies to tell their stories to consumers online – and a new marketing ecosystem will be created around AI. Bluefish is building the platform that helps brands engage consumers on this new AI channel, with powerful enterprise tools to manage AI brand safety and engage consumers with thoughtful and personalized AI marketing experiences.

Why Bluefish & Our Values

• Unique opportunity to join on the ground floor of a fast‑moving startup building at the center of AI
• Tackle challenging and abstract problems while disrupting the $300 BN legacy mar‑tech industry
• Join an experienced high‑performing team where you will have immediate ownership and impact
• Experience a true meritocracy with significant career growth upside as the business scales

Our Values

• Demonstrated grit and resourcefulness – you find creative solutions, adapt quickly, and aren’t afraid to roll up your sleeves in a fast‑paced, evolving environment.
• Thoughtful and strategic thinker with the ability to anticipate needs, ask the right questions, and deliver insights that truly drive value.
• Proven ability to collaborate across functions and roles, fostering open communication and shared ownership of outcomes.
• Commitment to craftsmanship – you take pride in delivering high‑quality work, paying attention to the small details while keeping the big picture in mind.
• Self‑starter with a proactive mindset and a strong sense of accountability – able to drive projects forward independently while staying aligned with team goals.
• Comfortable navigating ambiguity and learning new tools, processes, or technologies to get the job done.