AI Engineer

Blend360

About The Position

Blend is seeking a Senior AI Engineer to design, architect, and deploy advanced Generative AI solutions in production. The role contributes to LLM-based systems, agentic workflows, and applied AI initiatives, working closely with Engineering, Product, and MLOps teams. The ideal candidate brings hands-on technical expertise and sound software engineering practices, and can take AI solutions from design through production while balancing scalability, reliability, and business impact.

Requirements

Degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Strong expertise in transformer-based models and LLM architectures.
Proven experience designing and deploying applied machine learning or generative AI systems in production environments.
Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, OpenAI API, CrewAI, Azure Prompt Flow, AWS Bedrock Agents, or similar tools.
Advanced proficiency in Python and production-grade coding practices.
Experience with containerization, CI/CD pipelines, versioning, and cloud-native architectures.
Strong leadership skills and the ability to bridge rapid prototyping with scalable production deployment.
Excellent collaboration and communication skills, with experience working at the intersection of Data Science and Engineering.

Responsibilities

Contribute to the architecture and implementation of production-grade AI solutions using LLMs, transformer-based models, RAG pipelines, and agentic systems.
Design, develop, and optimize multi-step AI agents capable of tool and API invocation, reasoning chains, and state management.
Support deployment and optimization of AI-powered applications across AWS, Azure, or GCP, with attention to scalability, reliability, and cost-efficiency.
Contribute to best practices for prompt engineering, evaluation frameworks, and monitoring model performance, including latency, grounding, factuality, and cost.
Implement guardrails and Responsible AI practices, including prompt injection mitigation, content moderation, bias reduction, and safety controls.
Collaborate with Data Scientists, Software Engineers, and Product stakeholders to take AI solutions from prototype to production.
Share knowledge and support engineers in developing high-quality, modular, maintainable Python code.
Contribute to experimentation strategies, help define KPIs, and promote data-driven decision-making across AI initiatives.

Benefits

Certifications in AWS, Databricks, and Snowflake.
Access to AI learning paths, study plans, courses, and role-tailored certifications.
Access to Udemy Business courses.
English lessons to support professional communication.
Travel opportunities to attend industry conferences and meet clients.
Career development plans and mentorship programs.
Special day rewards for birthdays, work anniversaries, and other personal milestones.
Company-provided equipment.
Flexible working options.
Other benefits may vary according to location in LATAM.