Software Engineer – AI & Agentic Engineering

Job Summary:

The Senior Software Engineer – AI & Agentic Engineering is responsible for the technical implementation and engineering quality of a specific product team.

This is a hands-on software engineering role with responsibility for designing, developing, reviewing, testing, and operating production software. The Senior Software Engineer works closely with the Lead Software Engineer and plays a key role in adopting Agentic Engineering practices within the product team.

The candidate should not only be capable of writing software directly but also be able to effectively collaborate with AI coding agents and engineering agents, remaining accountable for the technical quality of the final implementation.

Each product team's Senior Software Engineer is expected to have the domain-specific competencies listed under Team-Specific Competencies .

Key Responsibilities:

Software Development

• Design, develop, test, and maintain production software; take ownership of critical technical components.
• Implement APIs, backend services, integrations, and application components.
• Write clean, maintainable, secure, and testable code; perform code reviews.
• Troubleshoot and resolve complex technical issues; optimize system performance and reliability.

System Design

• Translate product requirements into technical designs; participate in architecture design discussions and ADRs.
• Design APIs, data models, components, and integrations.
• Identify technical dependencies and risks.
• Ensure implementation aligns with reference architecture, shared platform components, and engineering standards.

Agentic Engineering

Use AI coding agents and engineering agents as part of the software development workflow:

• Break complex development work into agent-friendly tasks; provide clear context and instructions to engineering agents.
• Review and validate AI-generated code; ensure it follows architecture and coding standards.
• Use agents for code generation, refactoring, unit test generation, documentation, debugging assistance, code analysis, and repetitive development tasks.
• Validate security, correctness, and maintainability of agent-generated output.
• Improve engineering workflows with reusable prompts, tools, skills, and automation; share lessons learned with other teams.

AI agents are engineering tools. The Senior Software Engineer remains accountable for the technical quality of the final implementation.

AI Application Development

• Integrate AI capabilities provided by the AI Division and third-party providers (LLM APIs, RAG/KB services, ASR, TTS, embeddings) into product features.
• Implement application-level prompt, agent, and workflow logic for the product.
• Implement guardrails, fallback behavior, and observability (latency, cost, quality signals) at the application level.
• Escalate to the AI Division where deeper model or ML expertise is required; provide clear problem statements and data.

AI Product Evaluation

• Build and maintain the product-level evaluation harness for the team's AI features (golden sets, scenario tests, regression runs).
• Run evaluation before every release that changes prompts, models, retrieval, or agent logic; report results as part of release readiness.
• Work with the BA / APM on acceptance thresholds and with QA on automation and execution.

DevOps & Production

• Work with Git, CI/CD, Docker, containers, Kubernetes, logging, monitoring, distributed tracing, cloud and on-premise infrastructure, and automated testing.
• Provide deployment manifests, runbooks, and application-level SLOs and alerts to DevOps.
• Support application deployment, troubleshooting, and production issue resolution; participate in incident review.

Team Collaboration

• Work closely with the Senior BA / Assistant Product Manager on requirements and technical feasibility.
• Work with the Lead Software Engineer on architecture and engineering practices.
• Mentor Middle and Junior Engineers, including how to work effectively and safely with engineering agents.
• Participate in technical planning and estimation.

Required Qualifications:

• 5+ years of software development experience with strong hands-on programming skills.
• Good understanding of software architecture and system design.
• Experience developing backend services, APIs, or distributed systems.
• Good understanding of databases and integration patterns.
• Experience with Git, CI/CD, Docker, and modern development workflows.
• Hands-on experience building or integrating LLM-based features in production (at minimum: prompt design, API integration, handling non-deterministic output, basic evaluation).
• Experience using AI coding tools or agents in daily development.
• Strong debugging and problem-solving skills; ability to work independently on complex problems.

Preferred Qualifications:

• RAG, AI Agents / Agentic AI, AI orchestration frameworks
• Kubernetes, cloud platforms, on-premise deployment
• Real-time and high-concurrency systems
• Enterprise software; Contact Center platforms