Staff AI Engineer
Bp
Entity:
Technology
Job Family Group:
Job Description:
We’re looking for engineers who think holistically, automate relentlessly, and are fluent in the fast-moving world of AI tooling and infrastructure—but grounded in disciplined engineering principles.
Our AI Acceleration organization is building high-impact AI-powered applications that deliver real business value at speed. As a Staff AI Engineer, you’ll play a critical role in designing, building and deploying scalable AI-powered applications through solid software engineering excellence combined with pragmatic use of modern Data Science and AI capabilities. This is a role for seasoned engineers who are excited about applying AI in practical and scalable ways.
We’re looking for strong technical leaders who thrive at the intersection of disciplined software development and modern AI application. You should be comfortable working across the full lifecycle of a product—from ideation, architecture and data modelling to deployment, automation and operations—while navigating ambiguity and driving toward execution. Strong systems thinking, ownership mindset, and the ability to ship value fast are essential. You will work closely with engineers, data scientists, product managers, and business stakeholders to define problems, shape solutions, and ensure models perform reliably in the real world.
If you're passionate about building AI solutions that go beyond prototypes—solutions that are engineered for scale, reliability, and real-world value—AI Acceleration is the team for you.
Job Responsibilities
· Design, develop, and maintain production-grade AI applications and services using modern software engineering practices (CI/CD, testing, observability, cloud-native design).
· Define and implement foundational platforms (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise.
· Lead architectural decisions, bringing best practices in software development lifecycle, explainability, and responsible AI.
· Lead cross functional team initiatives—embedded projects with business stakeholders—to rapidly build and deploy AI solutions that solve high-priority problems.
· Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation) into robust applications.
· Champion automation in workflows—from data ingestion and preprocessing to model integration and deployment. Define their success criterias, metrics and standard operation procedures.
· Partner with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products.
· Stay current with emerging AI technologies, but prioritize practical application and delivery over experimental research.
· Contribute to the internal knowledge base, tooling libraries, and documentation to scale engineering practices across the organization.
· Mentor other engineer and data scientists and provide technical leadership across projects, helping raise the bar for rigor and impact.
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Job Qualifications
Required:
· 7+ years of professional software engineering experience; ability to independently design and ship complex systems in production.
· Strong programming skills in Python (preferred), Java, or similar languages, with experience in developing microservices, APIs, and backend systems.
· Solid understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices.
· Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents and crew of agents etc.).
· Experience with large language models (LLMs), vector-based search, retrieval-augmented generation (RAG), or unstructured data processing.
· Ability to move quickly while maintaining code quality, test coverage, and operational excellence.
· Strong problem-solving skills and a bias for action, with the ability to navigate ambiguity and lead through complexity.
· Strong experience with technical mentorship and cross-team influence.
· Ability to translate complex technical ideas into clear business insights and communicate effectively with cross-functional partners.
Preferred:
· Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems.
· Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits.
· Experience building reusable modeling components or contributing to internal ML platforms.
· Background in working with embedded teams or in forward-deployed environments where rapid iteration and close business collaboration are key.
· Proficiency in Python and common ML/data science libraries (e.g., scikit-learn, pandas, NumPy, PyTorch, TensorFlow).
· Solid knowledge of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, and statistical inference.
· Exposure to working with unstructured data (documents, conversations, images) and transforming it into usable structured formats.
· Experience building chatbots, search systems, or generative AI interfaces.
· Background in working within platform engineering or internal developer tools teams.
Travel Requirement
Relocation Assistance:
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Skills:
Legal Disclaimer:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp’s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us.
If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.