Full-Stack AI Systems Engineer

Weekday (YC W21); India; À distance; INR 700 000 - 1 300 000; Plein temps

Avantages offerts par ce poste

Competitive compensation

Strong growth potential

Support from top-tier global investors

Résumé du poste

A tech company in AI development is seeking an experienced engineer to build and maintain reinforcement learning environments. The ideal candidate has strong backend skills in TypeScript, Python, Go, or Java, along with a solid foundation in software engineering. You will work closely with a talented founding team and tackle exciting challenges in the AI ecosystem, with opportunities for remote work. Competitive compensation and growth potential are offered.

Qualifications

• Proven experience in small, fast-paced teams.
• Strong command of at least one major backend-focused stack.
• Background as a product engineer, platform engineer, or ML engineer.
• Ability to independently break down complex technical problems.
• Solid fundamentals in software engineering.

Responsabilités

• Build and maintain RL environments and sandbox systems.
• Rapidly onboard to new codebases every 4–6 weeks.
• Create engineering challenges and design mocks.
• Build internal tools, utilities, and frameworks.
• Contribute across the stack and primarily own backend behavior.

Connaissances

Backend engineering fundamentals (TypeScript / Python / Go / Java)

ML model training

ML model deployment

PyTorch

Full-stack development

Description du poste

Base Pay Range

Industry: Insurance. Seniority level: Associate level. Min Experience: 3 years. Location: Remote (India). Job Type: Full-time. This role is for one of our clients. We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.

What You’ll Bring

• Proven experience in small, fast-paced teams where individuals own large parts of the product (e.g., early-stage startups, founding engineering roles, CTO-level exposure).
• Strong command of at least one major backend-focused stack: TypeScript, Python, Go, or Java, with bonus points for TypeScript proficiency.
• Background as a product engineer, platform engineer, or ML engineer who has built real systems — not limited to infrastructure maintenance or pure data science.
• Ability to independently break down complex technical problems, debug unfamiliar systems, and accelerate development using tools like Cursor.
• Solid fundamentals in software engineering and the confidence to work inside large, unfamiliar codebases on short timelines.

What You’ll Work On

• Build and maintain RL environments and sandbox systems that help train advanced coding agents used by top AI labs.
• Rapidly onboard to new codebases every 4–6 weeks, develop a strong understanding, and design RL tasks and scenarios around them.
• Create engineering challenges, design mocks, write comprehensive test suites, and handle supporting infra pieces to deliver high-fidelity RL workflows.
• Build internal tools, utilities, and frameworks that enable the environment team to prototype and iterate significantly faster.
• Contribute across the stack when needed, while primarily owning backend behavior, system logic, and environment dynamics.

Why Join Us

• Work with an exceptionally skilled, deeply technical founding team with expertise in reinforcement learning, systems engineering, and large-scale product development.
• Contribute to building one of India’s most talented engineering groups.
• Collaborate directly with founders in a high-trust, high-ownership environment.
• Tackle some of the hardest and most exciting problems in the AI ecosystem, shaping the future of agentic systems.
• Competitive compensation, strong growth potential, and support from top-tier global investors.
• Bangalore-based in-person setup, with flexibility for extraordinary remote candidates.

Key Skills

• PyTorch
• ML model training
• ML model deployment
• Backend engineering fundamentals (TypeScript / Python / Go / Java)
• Full-stack development (as required)