1 day ago
Boston, MA, USA +36 moreMid Level
Responsibilities
- Build and ship production features across frontend, APIs, backend services, integrations, and data.
- Debug and resolve issues across application, data, and infrastructure boundaries.
- Develop, containerize, and deploy services on cloud platforms using Docker, Kubernetes, serverless, and managed cloud services.
- Apply infrastructure as code and help keep services healthy, observable, and recoverable in production.
- Write automated tests, resolve pipeline failures, and take changes through production.
- Design data access across relational and non-relational stores, APIs, object storage, and event platforms.
- Build retrieval and context layers using knowledge sources, embeddings, metadata, and context management.
- Integrate commercial and open models through APIs and enterprise AI platforms using tool calling, structured outputs, retrieval, and context engineering.
- Build and evaluate agent workflows with tools, memory, human checkpoints, and measures for accuracy, latency, safety, and cost.
- Use AI-native development techniques for code generation, testing, debugging, refactoring, documentation, and code comprehension.
- Participate in design reviews, code reviews, production troubleshooting, documentation, and development of reusable engineering patterns and tooling.
Requirements
- At least 3 years of professional software engineering experience building production software.
- At least 2 years of hands-on experience across more than one software stack layer.
- At least 3 years of programming experience in Java, Python, Go, TypeScript, JavaScript, C#, or another major language.
- At least 3 years of hands-on experience with AWS, Azure, or GCP, including deploying containerized services.
- At least 3 years of experience working in automated pipelines and writing automated tests.
- At least 1 year of experience building and shipping AI-enabled features or agent workflows using model APIs, tool calling, structured outputs, retrieval, and context engineering.
- At least 1 year of experience using AI coding tools for software development activities.
- Bachelor’s degree in Computer Science, Engineering, or equivalent; an associate degree requires at least 6 years of work experience, and equivalent work experience may satisfy the degree requirement with at least 12 years.
- Preferred qualifications include agent framework experience, AI evaluation or test-harness experience, infrastructure-as-code and observability experience, relevant cloud or AI certifications, client- or product-facing presentation experience, and ownership of features in startup, product-company, or hyperscaler environments.
- A public repository, portfolio, or open-source contribution featuring personally built agents, tools, or plugins is a bonus.
Benefits
- Medical, dental, vision, life, and long-term disability coverage.
- 401(k) plan, bonus opportunities, paid holidays, and paid time off.
- Travel may be required, varying from 25% to 75% based on business and client needs.
- The role is client-embedded and supports production work for enterprise customers.
Tech Stack
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.