Offer summary

Qualifications:

Advanced English proficiency (B2 or higher) for effective communication., Over 5 years of experience in software engineering, ML engineering, or AI engineering., Strong Python skills, especially in APIs and AI/ML libraries, along with experience in AWS services., Hands-on experience with vector databases and embedding techniques, and familiarity with OpenAI models..

Key responsibilities:

Build and deploy AI-driven systems using OpenAI and Amazon Bedrock.

Design and optimize vector search solutions and prototype LLM-based applications.

Develop scalable AI pipelines on AWS and integrate monitoring tools for performance tracking.

Collaborate with cross-functional teams to align technical work with business objectives and communicate effectively with stakeholders.

Job description

Job Opportunity only available for residents in Bogotá, Colombia.

As a AI Engineer, you will work across the full lifecycle of AI product development from prototyping and proof-of-concept, through to scalable production systems. You will drive innovation in a fast-moving environment, leveraging LLMs, custom embeddings, vector search, and LLMOps practices. Youll collaborate with Product, Research, and Engineering teams to create reliable, maintainable AI capabilities integrated seamlessly into our core products.

You will help shape our AI engineering best practices, contribute to infrastructure decisions, and play a pivotal role in our broader technical direction around AI/ML.

Qualifications

Required:

Advanced English for fluent communication (B2 or Higher).
5+ years of experience as a software engineer, ML engineer, or AI engineer.
Strong Python development skills, particularly around APIs, backend services, and AI/ML libraries.
Experience with AWS services (Lambda, S3, Bedrock, ECS, etc.) and cloud-native architecture.
Hands-on experience with vector databases and embedding techniques (e.g., pgvector, FAISS, Pinecone, or similar).
Experience building applications powered by OpenAI models and/or Bedrock foundation models, using frameworks like Langchain and LangGraph.
Ability to work autonomously to take projects from concept to production.
Excellent communication skills with the ability to explain technical details to diverse audiences.

Preferred:

Experience working in the private markets, fintech, or financial services sectors.
Prior experience integrating AI/ML into production-grade systems at scale.
Exposure to Retrieval-Augmented Generation (RAG) pipelines and prompt engineering.
Experience contributing to architectural decisions for AI-driven platforms.
Experience working in small teams (25 engineers).

Key Responsibilities

AI Engineering:
- Build and deploy AI-driven systems and applications using OpenAI, Amazon Bedrock, Langchain, and LangGraph.
- Design, implement, and optimize vector search solutions with pgvector and custom embeddings.
- Prototype, fine-tune, and productionize LLM-based and retrieval-augmented generation (RAG) solutions; develop input/output guardrails to ensure model safety, reliability, and alignment with business goals. Design and maintain robust evaluation pipelines to monitor model performance, correctness, and drift over time.

Infrastructure & Scaling:
- Develop scalable AI pipelines and infrastructure on AWS using Python, Pulumi/CDK, and Github Actions.
- Integrate tracing and experiment tracking tools (e.g., Weights & Biases, Langsmith) to monitor system behavior, performance metrics, and model quality over time.
Collaboration & Communication:
- Work closely with cross-functional partners in Product, Research, and Engineering to align technical work with business needs.
- Communicate technical concepts clearly to non-technical stakeholders and executive leadership.
Ownership:
- Operate across the full spectrum from prototype (0-1) to scalable, production-grade solutions.
- Contribute to decisions around architecture, tooling, and technology choices for AI initiatives.

What do we offer?