Senior Software Engineer - AI Engineering
WFA Digital Insight
As the demand for AI specialists continues to skyrocket, with a 25% growth in 2025, Mercury is at the forefront of this trend. This Senior Software Engineer - AI Engineering role stands out for its focus on building shared infrastructure and capability, enabling faster prototyping and iteration across the company. With the remote work landscape evolving, skills in AI engineering, platform development, and collaboration are in high demand. Before applying, candidates should be prepared to showcase their experience in building and deploying AI-powered systems, as well as their ability to communicate complex ideas to both technical and non-technical audiences.
Job Description
About the Role
The Senior Software Engineer - AI Engineering role at Mercury is a unique opportunity to be part of a team that is pushing the boundaries of what is possible with AI. As someone who is passionate about building and extending AI platforms, you will be responsible for taking the company's AI capabilities to the next level. This role matters because it will enable the company to accelerate its AI adoption and make a significant impact on the industry.The day-to-day responsibilities of this role will involve collaborating with a team of engineers to build and extend the company's internal AI platform and enablement layer. You will be working on complex systems, navigating platform engineering, infrastructure, and developer tooling, and communicating with both technical and non-technical audiences. The team is already making great progress, but they need someone with your skills and experience to help take it to the next level.
What You Will Do
- Build and evolve MCP servers that connect internal systems and data sources into a coherent interface for agents and engineers
- Expand and operate the LLM gateway infrastructure, including routing, rate limiting, cost attribution, and observability across teams
- Turn early patterns into durable defaults, including shared prompt libraries, guardrails, and policy-as-code, so teams can move fast safely
- Shape and maintain structured context artifacts, such as clean, reliable, agent-consumable data, so LLMs working in Mercury's systems can reason accurately about the domain
- Improve internal knowledge discoverability and retrieval, so both humans and agents can quickly find accurate answers
- Partner with domain teams to standardize key sources of truth and keep them fresh
- Build and refine sandbox environments and tooling that let engineers experiment with AI safely and at speed
- Create self-service scaffolding, so non-engineers, such as PMs, ops, and finance, can prototype and deploy AI-powered workflows with minimal hand-holding
- Build playgrounds and evaluation harnesses, so internal AI agents can be tested and iterated in controlled environments before hitting production
What We Are Looking For
- 5+ years of backend development experience in complex, production systems
- Fluency across programming languages and the ability to navigate platform engineering, infrastructure, and developer tooling
- Hands-on experience building LLM-powered systems, including RAG pipelines, agents, and eval frameworks, and having shipped at least one of these to production
- Understanding of the real tradeoffs in AI deployments, including cost modeling, observability, latency, and safety
- High-agency and self-directed, with the ability to operate effectively without tightly-defined scope and find the highest-leverage work
- Strong communication skills, with the ability to explain complex ideas to both technical and non-technical audiences
- Experience working in a remote or distributed team environment
- Strong problem-solving skills, with the ability to debug complex issues and optimize system performance
Nice to Have
- Experience with specific AI frameworks and tools, such as TensorFlow or PyTorch
- Knowledge of cloud computing platforms, such as AWS or GCP
- Experience with containerization and orchestration tools, such as Docker and Kubernetes
- Familiarity with agile development methodologies and version control systems, such as Git
Benefits and Perks
- Competitive salary and equity package
- Comprehensive benefits package, including health, dental, and vision insurance
- Flexible PTO policy and remote work stipend
- Opportunities for professional growth and development, including training and conference attendance
- Collaborative and dynamic work environment with a team of experienced engineers
- Access to the latest tools and technologies, including AI and machine learning frameworks
- Recognition and rewards for outstanding performance and contributions to the company
How to Stand Out
- Make sure to highlight your experience with AI-powered systems and LLMs in your resume and cover letter, and be prepared to provide specific examples of your work in these areas.
- Showcase your ability to communicate complex ideas to both technical and non-technical audiences, and be prepared to explain your thought process and design decisions.
- Be prepared to discuss your experience with platform engineering, infrastructure, and developer tooling, and how you have applied these skills in previous roles.
- Research the company and the role thoroughly, and be prepared to ask informed questions during the interview process.
- Consider creating a portfolio or GitHub repository that showcases your work and projects, and be prepared to discuss your contributions and accomplishments.
- Be prepared to discuss your experience working in a remote or distributed team environment, and how you stay motivated and productive in these settings.
- Don't be afraid to ask about the company culture and values, and how they support the well-being and growth of their employees.
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