SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Kantiv is seeking a Senior Software Engineer with 4–5 years of experience to lead technical work on the chat team. This is a hands-on role combining strong programming fundamentals with practical expertise in agentic systems and LLM applications.
You will own the technical design and delivery of chat-team projects, shape engineering priorities and standards, and maintain a high bar for code quality. You'll write production Python, design clear abstractions, and review pull requests for correctness, maintainability, and design quality. A key part of the role is mentoring junior developers through thoughtful guidance and helping them strengthen their programming and system-design judgment.
You'll diagnose production issues across application code, agent workflows, prompts, models, data, and infrastructure. You'll improve the reliability, observability, latency, and cost of chat systems. You'll also take initiative in making the team more AI-native by improving how the team uses coding agents throughout the development lifecycle, including mentoring others in effective agentic coding workflows.
Success means the team makes clearer technical decisions, projects have simple designs with well-defined boundaries and useful tests, code reviews catch meaningful issues early, junior developers grow more independent, the team develops effective agentic coding practices, production issues become easier to diagnose, and the codebase becomes easier to understand and operate.
REQUIREMENTS:
- Approximately 4–5 years of professional software engineering experience
- Strong proficiency in Python, including writing idiomatic, typed, testable, and maintainable production code
- Strong programming fundamentals and consistently sound engineering judgment
- Experience designing, delivering, and operating production systems
- Ability to create useful abstractions while keeping systems simple and understandable
- Strong knowledge of API design, data modeling, concurrency, error handling, and observability
- Experience writing effective automated tests (e.g., pytest)
- Ability to review code beyond surface-level concerns and explain reasoning behind suggested changes
- Experience mentoring junior developers and improving the quality of their work
- Comfort taking ownership, identifying opportunities, and driving improvements across a team
- Clear written and verbal communication
- Hands-on experience building LLM or agentic applications (required). Relevant experience may include: building tool-calling or multi-step workflows using LangGraph or comparable frameworks; designing conversation state, context management, and execution flows; working with model APIs, structured outputs, retrieval, and grounding; supporting streaming responses and asynchronous execution; evaluating prompts, models, and end-to-end agent behavior; instrumenting and debugging LLM applications with Langfuse, LangSmith, or similar platforms; managing reliability, latency, and cost of production LLM systems
- Power user of agentic coding workflows with ability to use coding agents as engineering tools rather than simple code generators. Should be able to use coding agents effectively across exploration, planning, implementation, testing, debugging, and review; provide agents with right context, constraints, and verification steps; critically evaluate generated code for correctness, security, maintainability, and unnecessary complexity; design development workflows that keep engineers accountable; identify repeatable team workflows that can be improved through agents and automation; teach junior developers how to use coding agents effectively without weakening engineering fundamentals; lead practical initiatives that make the team faster and more AI-native
