AI Pipeline Developer

Role Overview We are looking for an AI Pipeline Developer to design, build, maintain, and improve AI-driven development pipelines, with a strong focus on code-generation workflows. The main responsibility of this role is to work as a developer for AI pipelines. The secondary responsibility is to act as the custodian of AI pipelines that generate code, ensuring they are reliable, secure, maintainable, and aligned with engineering standards. This role requires strong computer science fundamentals and the ability to work across multiple programming languages. In the AI era, the barrier between programming languages is lower, so the ideal candidate should not be locked into a single language or technology stack. Key Responsibilities Design, build, and maintain AI pipelines that generate, transform, validate, test, and deploy code.Act as custodian of AI code-generation pipelines, ensuring quality, reliability, security, and maintainability.Work across multiple programming languages such as Go, Rust, TypeScript, Java, Python, and others as needed.Review, validate, and improve AI-generated code for correctness, performance, architecture, security, and maintainability.Build integrations between LLM APIs, AI tools, developer platforms, CI/CD systems, databases, and internal services.Implement guardrails, validation steps, automated tests, quality gates, and monitoring for AI- generated outputs.Develop tooling to improve developer productivity through AI-assisted workflows.Debug complex issues across services, languages, runtimes, infrastructure, and AI pipeline components.Collaborate with architects, developers, product teams, and stakeholders to translate requirements into reliable systems.Continuously evaluate new AI tools, frameworks, patterns, and engineering practices for practical adoption. Required Skills and Experience Strong fundamentals in computer science, software engineering, algorithms, data structures, systems design, and debugging.Solid backend development experience with APIs, services, databases, testing, version control, and CI/CD.Comfortable working across different programming languages, including but not limited to Go, Rust, TypeScript, Java, and Python.Practical understanding of LLM APIs, model providers, prompt design, structured outputs, context management, and tool/function calling.Familiarity with AI agents, multi-step workflows, RAG, embeddings, vector databases, evaluation, and guardrails.Experience or familiarity with AI orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar.Good understanding of relational and non-relational databases, data modeling, queries, indexing, and performance considerations.Ability to critically assess AI-generated code and identify flaws, risks, edge cases, and improvement opportunities.Strong knowledge of software quality practices, including automated testing, static analysis, code review, observability, and secure coding.Ability to learn quickly, adapt to new tools, and work in a fast-changing technical environment. Preferred Qualifications Experience building AI agents, code-generation tools, developer platforms, automation systems, or internal engineering tools.Experience integrating AI capabilities into CI/CD pipelines or software development workflows.Familiarity with containers, Kubernetes, cloud platforms, infrastructure-as-code, and distributed systems.Knowledge of sandboxing, policy enforcement, secrets handling, and security controls for AI-generated code.Experience with vector databases, retrieval systems, workflow engines, or event-driven architectures.Background in platform engineering, DevOps, developer experience, or software architecture. Ideal Candidate Profile The ideal candidate is a strong software developer with broad technical fundamentals, not limited to one programming language or framework. They are comfortable reading, writing, and reviewing code across multiple languages and can quickly understand unfamiliar systems. They understand how to use AI tools practically in software engineering, especially for building and maintaining AI Pipeline Developer Job Descriptioncode-generation pipelines. They are detail-oriented, security-conscious, and capable of balancing speed, automation, and engineering quality. Success in This Role Looks Like AI code-generation pipelines are reliable, maintainable, and trusted by engineering teams.Generated code is validated through automated checks, tests, reviews, and guardrails. Developers can use AI-assisted workflows safely and productively.Pipeline failures, risks, and quality issues are identified and resolved quickly.New AI tools and patterns are evaluated pragmatically and adopted where they provide real engineering value.