Senior Software Engineer specialized in Generative AI- Mexico Only NO LATAM

Role Summary

Work at DaCodes!

We are a firm of experts in high-impact software and digital transformation.

For more than 10 years we have created solutions focused on technology and innovation thanks to our team of almost 300 talented #DaCoders, including developers, architects, UX/UI designers, PMs, QA Testers and data and Artificial Intelligence specialists. Our team collaborates on projects with clients in LATAM and the United States, promoting high-impact technological initiatives.

At DaCodes you will have the opportunity to work with cutting-edge technologies, participate in applied Artificial Intelligence projects and collaborate with multidisciplinary teams that develop solutions for leading organizations in the region.

Our DaCoders have a direct impact on the success of our clients. You will have the opportunity to design, build and evolve AI solutions that will be used in productive environments and solve real business problems.

Are you interested?

About the project

You will be part of the Data & AI team of one of our most important clients in the financial sector.

We are looking for a Senior AI Software Engineer with experience building Generative Artificial Intelligence solutions for production. The role is aimed at designing and implementing applications based on LLMs, agents and cloud architectures, integrating AI models with corporate platforms, APIs, data sources and critical business processes.

We're not just looking for experience consuming models through APIs; We are looking for a profile with engineering criteria capable of designing complete solutions, selecting the appropriate architecture for each use case and operating AI applications in productive environments.

Practical experience implementing solutions with

• Language Models (LLMs)
• Prompt Engineering
• AI Agents
• LangChain, LangGraph or equivalent frameworks
• Tool Calling
• Agent Orchestration
• Integration of foundational models (GPT, Claude, Gemini, Llama or similar)

Experience implementing solutions with

• Embeddings
• Vector bases
• Retrieval-Augmented Generation (RAG)

Desirable experience with

• hybrid search
• reranking
• retrieval quality assessment

The ability to justify when RAG adds value and when it is not necessary will be especially valued.

Cloud

Practical experience designing and implementing solutions on AWS and/or Azure.

Experience integrating components such as

• APIs
• serverless services
• storage
• authentication
• queues/events
• databases
• observability

More than knowing specific services, we seek the ability to design cloud architectures for AI applications.

AI Solutions Operation (LLMOps)

Experience in

• Docker
• CI/CD
• versioning
• monitoring
• observability
• logging
• cost optimization

Desirable experience with tools such as

• LangFuse
• Lang Smith
• OpenTelemetry
• Azure Monitor
• CloudWatch
• Technical fundamentals

Responsibilities

• Design and implement production-ready Generative AI applications.
• Build solutions based on LLMs, agents and RAG architectures when the use case requires it.
• Design APIs, microservices, and reusable components to accelerate new AI initiatives.
• Integrate AI models with business systems, cloud platforms, and structured and unstructured data sources.
• Design cloud architectures using AWS or Azure considering security, scalability, observability and maintainability.
• Implement information retrieval mechanisms using embeddings and vector bases.
• Design model selection strategies considering accuracy, cost, latency and context.
• Implement LLMOps practices for deployment, monitoring, versioning and operation of solutions based on LLMs.
• Participate in the definition of technical architecture together with other engineers and product teams.
• Collaborate with stakeholders to convert business needs into technical solutions.

Expected results

• AI solutions successfully deployed in production.
• Reusable components for new AI initiatives.
• Maintainable and scalable cloud architectures.
• Solutions with observability, monitoring and quality metrics.
• Continuous optimization of cost, latency and model accuracy.
• Efficient integration between business platforms and AI components.

Requirements

• +5 years developing software.
• +3 years building Generative AI solutions for production.
• Experience implementing end-to-end solutions, from prototype to production.
• Experience collaborating with multidisciplinary teams (Product, UX, Data Science, Backend).
• Experience in regulated industries (Fintech, banking, insurance or healthcare) desirable.
• Software Development
• Essential
• Python
• SQL
• REST APIs
• Microservices
• Docker
• Git

Desirable

Node.js

Generative Artificial Intelligence

We expect solid understanding of concepts such as

• Transformers
• Embeddings
• Attention
• Context Window
• temperature
• Tokenization
• Fine-tuning
• LoRA
• RAG

We are not looking for academic research, but we are looking for the ability to explain these concepts and make engineering decisions from them.

We will especially value

• Design of complete architectures for AI applications.
• Development of solutions with agents in production.
• Integration of AI with business systems.
• Observability and operation of applications based on LLMs.
• Cost and performance optimization.
• Ability to explain and justify technical decisions.

Profile we are looking for

• We are looking for a profile with a builder mentality and a strong engineering orientation.
• We want someone capable of designing and building complete AI solutions, from integration with cloud platforms to operation in production, making informed technical decisions and prioritizing simplicity, maintainability and business value.
• We especially value profiles who know how to distinguish between experimenting with new technologies and selecting the most appropriate solution to solve a real problem.

Training

• Systems Engineering, Computer Science, Software or related careers.
• Postgraduate or specialization in AI, Machine Learning or quantitative disciplines will be a plus.
• Modality
• Remote
• English
• Intermediate – Advanced

Benefits

• 🚀 Integration to global brands and disruptive startups.
• 🏡 Remote work/Home office.
• ⏳ Schedule adjusted to the assigned work cell/project.
• 📅 I work from Monday to Friday.
• 🏥 Major medical expense insurance (applies to Mexico).
• 🛡️ Life insurance (applies to Mexico).
• 🌎 Multicultural work teams.
• 🎓 Access to courses and certifications.
• 📢 Meetups with special guests from the IT area.
• 📡 Virtual integration events and interest groups.
• 📢 English classes.
• 🏆 Opportunities within our different lines of business.
• 🏅 Proudly certified as a Great Place to Work.

Capacity for

• deciding when to use Generative AI and when a deterministic solution is sufficient.
• select models considering cost, latency, accuracy and project constraints.
• RAG and Information Recovery