About the Role

We are looking for Women AI Engineers who want to help
shape the future of Financial Services clients and our company. As part of the
team, you will get to

· Work directly
with our founding team and be a core member.

· Apply the
latest AI techniques to solve real problems faced by Financial Services
clients.

· Design,
build, and refine datasets to evaluate and continuously improve our solutions.

· Participate
in strategy and product ideation sessions, influencing our product and solution
roadmap.

Key Responsibilities

· Agentic AI Development: Work on building scalable multi -modal Large
Language Model (LLM) based AI agents, leveraging frameworks such as LangGraph,
Microsoft Autogen, or Crewai.

· AI Research and Innovation: Research and build innovative solutions to
relevant AI problems, including Retrieval -Augmented Generation (RAG), semantic
search, knowledge representation, tool usage, fine -tuning, and reasoning in
LLMs.

· Technical Expertise: Proficiency in a technology stack that includes
Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres,
SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript,



and React.

· LLM and NLP Experience: Hands -on experience working with LLMs, RAG
architectures, Natural Language Processing (NLP), or applying Machine Learning
to solve real -world problems.

· Dataset Development: Strong track record of building datasets for
training and/or evaluating machine learning models.

· Customer Focus: Enjoy diving deep into the domain, understanding
the problem, and focusing on delivering value to the customer.

· Adaptability: Thrive in a fast -paced workplace and are
excited about joining an early -stage venture.

· Model Deployment and Management: Automate model deployment, monitoring, and
retraining processes.

· Collaboration and Optimization: Collaborate with data scientists to review,
refactor, and optimize machine learning code.

· Version Control and Governance: Implement version control and governance for
models and data.

Required Qualifications:

- Bachelor's
degree in computer science, Software Engineering, or a related field

- 2 -4 years of experience in MLOps, DevOps, or related roles

- Have
strong programming experience and familiarity with Python based deep learning
frameworks like Pytorch, JAX, Tensorflow

- Have
strong familiarity and knowledge of machine learning concepts

- Proficiency
in cloud platforms (AWS, Azure, or GCP) and infrastructure -as -code tools like
Terraform



Desired
Skills:

- You have experience with technology stack: Python,
LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy,
Alembic, OpenAI, Docker, Azure, Typescript, React.

- Knowledge of data pipeline orchestration
tools like Apache Airflow or Prefect

- Familiarity with software testing and
test automation practices

- Understanding
of ethical considerations in machine learning deployments

- Strong
problem -solving skills and ability to work in a fast -paced environment