Staff Software Engineer (GenAI Innovation/ Forward deployed)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer (GenAI Innovation / Forward Deployed) based in the United States.

As a Staff Software Engineer, you will lead the development of innovative systems that turn emerging generative AI capabilities into practical, scalable business solutions. You’ll work in a forward-deployed environment where experimentation, rapid prototyping, and measurable business impact are central to the role. The position spans backend services, APIs, databases, cloud infrastructure, and web experiences, giving you broad technical ownership from concept through production. You’ll explore frontier AI technologies while applying sound engineering judgment to determine where AI can-and cannot-create meaningful value. Working across a complex, matrixed organization, you’ll partner with multidisciplinary teams to move ideas quickly from experimentation into reliable production systems. You’ll also leverage AI-assisted development tools to accelerate engineering workflows without compromising quality. This is an opportunity to shape how next-generation AI is applied across large-scale media, entertainment, and consumer-facing businesses.

Accountabilities:

• Research, prototype, and evaluate emerging generative AI technologies, translating promising capabilities into solutions with measurable business value and return on investment.
• Assess proposed AI use cases critically, distinguishing genuine AI opportunities from problems that are better solved through conventional technology or process improvements.
• Lead technical development from concept through deployment, independently taking ownership of applications and collaborating with cross-functional partners as needed.
• Design and build scalable backend services, business logic, data layers, and APIs using established engineering patterns and organizational standards.
• Develop and maintain databases and storage solutions across SQL and NoSQL environments.
• Build end-to-end features spanning web frontends, APIs, backend services, and underlying data systems.
• Integrate foundation models and agentic AI capabilities into applications using appropriate tooling, instrumentation, retrieval-augmented generation (RAG), and model-selection approaches.
• Develop automated tests and maintain high standards for reliability, code quality, maintainability, and security-including careful review of AI- or agent-generated code.
• Deploy applications to cloud environments and troubleshoot application, infrastructure, configuration, and networking issues.
• Use code-generation and test-generation technologies to accelerate development while maintaining rigorous engineering standards.
• Collaborate across multidisciplinary and matrixed teams, building alignment through clear communication, technical expertise, and strong interpersonal skills.
• Translate ambiguous business needs into practical technical requirements, architectures, and scalable implementations.
• Adapt quickly to changing priorities, incorporate feedback, and continuously improve solutions as new information and technologies emerge.

Requirements

• 6+ years of professional experience in backend or full-stack software development, supported by a strong portfolio of relevant technical work.
• Demonstrated systems-thinking ability, with experience addressing underlying systemic problems rather than simply treating symptoms.
• Proven ability to take an application from an initial idea through design, implementation, testing, and production delivery.
• Strong experience with Python for application development, along with AWS, database technologies, and SQL.
• Familiarity with the broader Python ecosystem and tools used for software development, testing, build automation, and deployment.
• Strong understanding of machine learning practices relevant to foundation-model integration, including model selection, RAG patterns, tooling, instrumentation, and evaluation.
• Exposure to fine-tuning, deep learning, model training, or related AI/ML concepts.
• Practical experience designing, integrating, and consuming APIs across backend and frontend applications.
• Experience building scalable technical architectures and communicating architectural concepts clearly to technical and non-technical stakeholders.
• Familiarity with large language models, AI-generated content, and the evolving ecosystem of LLM application-development tools such as LangChain.
• Ability to work effectively within secured internal networks and complex cloud environments.
• Strong analytical and problem-solving skills, particularly when requirements are ambiguous or evolving.
• Ability to distinguish user preferences from essential technical or business requirements and independently identify appropriate solutions.
• Excellent communication and collaboration skills, with the ability to navigate complex organizational structures and work effectively across teams.
• High adaptability and comfort operating in a rapidly changing technology landscape.
• Strong engineering judgment, curiosity, ownership, and willingness to experiment with emerging technologies.
• Ability to work with agility, respond constructively to feedback, and adjust priorities as business needs evolve.

Benefits

• Competitive base salary of $130,000-$170,000, with eligibility for a bonus.
• Fully remote work arrangement within the United States.
• Medical, dental, and vision insurance.
• 401(k) retirement savings plan.
• Paid leave.
• Tuition reimbursement.
• Employee discounts and a variety of additional perks and benefits.
• Opportunity to work at the forefront of generative AI and foundation-model application development.
• Broad technical ownership spanning AI, backend systems, APIs, databases, cloud infrastructure, and web applications.
• Opportunity to collaborate with multidisciplinary teams and apply emerging technologies to large-scale, real-world business challenges.
• Ongoing opportunity to learn, experiment, and influence how AI-enabled products and systems are built and deployed.