Senior LLM Engineer
il y a 2 semaines
Role Summary
:
We are looking for a
Senior LLM Engineer
with deep expertise in
Large Language Model development, orchestration, and application engineering
. The ideal candidate has 3–5 years of hands-on experience building and deploying AI systems using
LangChain
,
LangGraph
, and related frameworks. You will be responsible for designing, implementing, and optimizing complex, multi-agent LLM applications that drive real business value.
Key Responsibilities
:
- Design, build, and optimize
LLM-based systems
leveraging
LangChain, LangGraph, and vector databases
. - Develop and maintain
modular prompt pipelines, agents, and tools
that enable dynamic reasoning and contextual understanding. - Integrate
LLMs with APIs, databases, and internal tools
for seamless automation and data interaction. - Fine-tune, evaluate, and deploy
foundation models
(e.g., OpenAI, Anthropic, Mistral, Llama) for domain-specific applications. - Implement
retrieval-augmented generation (RAG)
and
knowledge graph reasoning
pipelines. - Collaborate with cross-functional teams — product managers, data engineers, and researchers — to bring LLM-driven products to life.
- Contribute to
LLM system architecture design
, ensuring scalability, maintainability, and performance. - Stay current with emerging
AI frameworks, model APIs, and orchestration patterns
.
Key requirements
:
- Master's degree
or
Degree
in Computer Science, Artificial Intelligence, or a related field. - 3–5 years of experience developing with
LangChain
and
LangGraph
in production environments. - Strong proficiency in
Python/Java Scripts
and
LLM APIs
(OpenAI, Anthropic, Hugging Face, etc.). - Experience with
RAG pipelines, embeddings, and vector databases
. - Solid understanding of
prompt engineering
,
LLM evaluation
, and
tool/agent design
. - Experience with
Docker
,
Git
, and modern cloud environments (e.g. Azure or AWS etc.). - Experience with
multi-agent systems
,
function calling
, and
graph-based orchestration
. - Familiarity with
LangSmith
or
LLMOps
tools for observability and performance tracking. - Knowledge of
data pipelines, ETL systems, or microservice architectures
. - Prior work in
AI product development
,
chatbot orchestration
, or
automation systems
.
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