Senior AI Engineer - Chat & Agent Systems

Jobgether; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Fully remote

Full-time

Technical leadership

AI projects

Engineering standards

Job summary

Jobgether is seeking a senior software engineer to lead the technical design and delivery of chat-team projects, while remaining closely involved in implementation. You will own architecture, set engineering priorities, and translate product requirements into scalable designs.

You will write high-quality Python, review code, mentor juniors, and drive reliability, observability, and cost improvements across production LLM systems.

Qualifications

• Approximately 4-5 years of professional software engineering experience.
• Strong proficiency in Python, including idiomatic, typed, testable, and maintainable production code.
• Experience designing, delivering, and operating production systems.
• Strong understanding of API design, data modeling, concurrency, error handling, and observability.
• Experience writing automated tests using tools such as pytest.
• Ability to conduct meaningful code reviews and clearly explain technical recommendations.
• Experience mentoring junior developers and helping improve their engineering capabilities.

Responsibilities

• Own the technical design, architecture, and delivery of chat-team projects.
• Help define engineering priorities, standards, and day-to-day technical decisions.
• Translate product requirements into simple, scalable, and maintainable system designs.
• Write high-quality production Python code and develop clear abstractions without unnecessary complexity.
• Review pull requests, assessing correctness, maintainability, test coverage, and overall design quality.
• Mentor junior developers, providing practical guidance on programming fundamentals, system design, and code quality.
• Diagnose production issues across application code, agent workflows, prompts, models, data, and infrastructure.
• Improve system reliability, observability, latency, and operating costs.
• Promote effective use of AI coding agents across exploration, planning, implementation, testing, debugging, and code review.
• Identify opportunities to automate and improve engineering workflows while maintaining accountability for code quality.
• Help the team adopt responsible, effective agentic coding practices and become more AI-native.

Skills

Python

Code reviews

System design

Testing (pytest)

Mentoring

Observability

Communication

Tools

LangGraph

LangSmith

APIs

Job description

Accountabilities

You will lead the technical design and delivery of chat-team projects while remaining closely involved in implementation. Your responsibilities will include:

• Own the technical design, architecture, and delivery of chat-team projects.
• Help define engineering priorities, standards, and day-to-day technical decisions.
• Translate product requirements into simple, scalable, and maintainable system designs.
• Write high-quality production Python code and develop clear abstractions without unnecessary complexity.
• Review pull requests, assessing correctness, maintainability, test coverage, and overall design quality.
• Mentor junior developers, providing practical guidance on programming fundamentals, system design, and code quality.
• Diagnose production issues across application code, agent workflows, prompts, models, data, and infrastructure.
• Improve system reliability, observability, latency, and operating costs.
• Promote effective use of AI coding agents across exploration, planning, implementation, testing, debugging, and code review.
• Identify opportunities to automate and improve engineering workflows while maintaining accountability for code quality.
• Help the team adopt responsible, effective agentic coding practices and become more AI-native.

Requirements

The ideal candidate combines strong software engineering fundamentals with hands‑on experience building LLM‑powered applications and using AI coding agents. The following qualifications and skills are expected:

• Approximately 4-5 years of professional software engineering experience.
• Strong proficiency in Python, including idiomatic, typed, testable, and maintainable production code.
• Solid programming fundamentals and consistently sound engineering judgment.
• Experience designing, delivering, and operating production systems.
• Strong understanding of API design, data modeling, concurrency, error handling, and observability.
• Ability to create useful abstractions while keeping systems simple and understandable.
• Experience writing automated tests using tools such as pytest.
• Ability to conduct meaningful code reviews and clearly explain technical recommendations.
• Experience mentoring junior developers and helping improve their engineering capabilities.
• Strong ownership, initiative, problem‑solving skills, and the ability to drive improvements across a team.
• Clear written and verbal communication skills.

Agentic Systems Experience

Hands‑on experience building LLM‑powered or agentic applications is required. Relevant experience includes:

• Building tool‑calling or multi‑step workflows using LangGraph or comparable agent frameworks.
• Designing conversation state, context management, and execution flows.
• Working with model APIs, structured outputs, retrieval, and grounding techniques.
• 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 observability platforms.
• Managing the reliability, latency, and cost of production LLM systems.

Expertise in every named tool is not expected. A strong understanding of the underlying engineering principles and the ability to adapt as the ecosystem evolves are more important.

Agentic Coding Experience

The candidate should be highly proficient in agentic coding workflows and understand how to use coding agents as engineering tools rather than simply as code generators. This includes:

• Using coding agents effectively for exploration, planning, implementation, testing, debugging, and code review.
• Providing agents with appropriate context, constraints, and verification steps.
• Critically evaluating generated code for correctness, security, maintainability, and unnecessary complexity.
• Designing development workflows that ensure engineers remain accountable for the code produced.
• Identifying repeatable team processes that can be improved through agents and automation.
• Teaching junior developers to use coding agents effectively without compromising their engineering fundamentals.
• Leading practical initiatives that improve development speed and help establish AI‑native engineering practices.

Success in this role will be reflected in clearer technical decisions, simpler system designs, stronger test coverage, more effective code reviews, and increasingly independent junior developers. You will also help make production issues easier to diagnose and resolve, establish responsible AI‑assisted development practices, and improve the long‑term maintainability and reliability of the codebase.

Benefits

• Fully remote position based in India.
• Full‑time employment.
• Hands‑on technical leadership and ownership of key engineering projects.
• Opportunity to shape engineering standards and influence the team's technical direction.
• Opportunity to work on production‑grade AI and agentic systems.
• Opportunity to mentor developers and help advance AI‑native engineering practices.