Senior AI/LLM Engineer (Python) at Kake

Confirmed open

Kake is hiring a senior ai/llm engineer (python) focused on Python AI and large language model engineering.

Kake

Location: Remote
Advertised region: Worldwide
Work arrangement: remote
Technologies: Python, Docker, PyTorch, TensorFlow

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Role overview

Senior AI/LLM Engineer (Python) - Remote

Kake is a remote-first company and a people-first global community of senior engineers. Kake engineers are behind some of the world’s most innovative products (Brands you’ve heard!), from Fortune 500 to fast-growing companies. We believe it’s not where your table is, but what you bring to the table that matters. Our community spans 45,000+ engineers across 55+ countries; join a culture where great people stay, grow, and thrive (and love eating kake!).

Senior AI/LLM Engineers with strong Python experience, skilled in designing, building, and productionizing LLM-powered applications and AI systems at scale. It's a great fit for people who enjoy working at the intersection of software engineering and applied AI, and who take ownership from prototyping through production deployment.

Design, build, and deploy LLM-powered features and applications using Python.

Develop and maintain backend services and APIs (e.g., FastAPI) that expose AI/LLM capabilities to other systems.

Build and optimize RAG pipelines, including embeddings, vector search, and retrieval strategies.

Design, test, and iterate on prompts, agents, and orchestration flows using frameworks such as LangChain, LlamaIndex, or similar.

Integrate with LLM providers and APIs (e.g., OpenAI, Anthropic, open-source models) and manage tradeoffs around cost, latency, and quality.

Evaluate model outputs systematically, building tooling and metrics to test accuracy, safety, and regression across iterations.

Work with containerized environments and data infrastructure (e.g., PostgreSQL, Redis, vector databases) to support reliable AI systems in production.

Collaborate with cross-functional stakeholders to translate ambiguous product needs into technically sound AI solutions.

Strong proficiency in Python and experience with FastAPI or similar backend frameworks.

Responsibilities

Design, build or review technical systems for Python AI and large language model engineering.
Collaborate with customers, product and engineering stakeholders.
Improve reliability, testing, documentation and delivery quality.
Translate complex requirements into practical, maintainable solutions.

Qualifications

Senior AI/LLM Engineers with strong Python experience, skilled in designing, building, and productionizing LLM-powered applications and AI systems at scale. It's a great fit for people who enjoy working at the intersection of software engineering and applied AI, and who take ownership from prototyping through production deployment.
Design, build, and deploy LLM-powered features and applications using Python.
Develop and maintain backend services and APIs (e.g., FastAPI) that expose AI/LLM capabilities to other systems.
Build and optimize RAG pipelines, including embeddings, vector search, and retrieval strategies.
Design, test, and iterate on prompts, agents, and orchestration flows using frameworks such as LangChain, LlamaIndex, or similar.
Integrate with LLM providers and APIs (e.g., OpenAI, Anthropic, open-source models) and manage tradeoffs around cost, latency, and quality.
Evaluate model outputs systematically, building tooling and metrics to test accuracy, safety, and regression across iterations.
Work with containerized environments and data infrastructure (e.g., PostgreSQL, Redis, vector databases) to support reliable AI systems in production.
Collaborate with cross-functional stakeholders to translate ambiguous product needs into technically sound AI solutions.
Strong proficiency in Python and experience with FastAPI or similar backend frameworks.
Experience working with LLM APIs (e.g., OpenAI, Anthropic, or similar) and frameworks such as LangChain or LlamaIndex.
Experience with RAG architectures , embeddings, and vector databases (e.g., Pinecone, Weaviate, pgvector, or similar).
Hands-on experience with Docker and containerized development environments.
Experience working with PostgreSQL, Redis, or similar data stores.
Strong experience writing functional and integration tests, including evaluation frameworks for AI/LLM output quality.
Excellent written and verbal communication skills in English.

Technology in this role

Python: Python Docker PyTorch .
Docker: Python Docker PyTorch .
PyTorch: Python Docker PyTorch .
TensorFlow: Python Docker PyTorch .
PostgreSQL: Work with containerized environments and data infrastructure (e.g., PostgreSQL, Redis, vector databases) to support reliable AI systems in .
Redis: Work with containerized environments and data infrastructure (e.g., PostgreSQL, Redis, vector databases) to support reliable AI systems in .
Kafka: • Experience with distributed systems, streaming (e.g., Kafka), or large-scale .
scikit-learn: • Background in machine learning fundamentals (e.g., scikit-learn, PyTorch, or .
LLM: Senior AI/LLM Engineer (Python) - Remote Kake is a remote-first company and a people-first global community of senior .
RAG: Build and optimize RAG pipelines, including embeddings, vector search, and retrieval .
LangChain: Design, test, and iterate on prompts, agents, and orchestration flows using frameworks such as LangChain, LlamaIndex, or .
FastAPI: Develop and maintain backend services and APIs (e.g., FastAPI) that expose AI/LLM capabilities to other .

Benefits

Worldwide or US-remote arrangement as stated in the official posting.
Opportunity to work on software, AI or technical delivery projects.

About Kake

Kake describes itself as a remote-first community of experienced software engineers that helps client teams add individual engineers or full engineering groups. Its model combines technical vetting and human selection with AI-supported processes; Kake engineers work as dedicated members of client teams rather than as a separate outsourced delivery queue.

The company recruits across frontend, backend, mobile, quality engineering, data and DevOps. Its public hiring pages emphasize end-to-end ownership, collaboration with product and design, and engineering judgment. The exact client, product, team structure and employment terms can vary by opening, so candidates should verify those specifics in the individual listing.

Employer website

How to apply

Review the original posting and apply through the employer’s careers page.

View source and apply

Source checked: 2026-10-09

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