Daniel Alba / Barcelona metropolitan area
Tech Lead
Architecture definition, day-to-day team guidance, and direct development in the codebase.
The current focus as Tech Lead at evoluxia started with the challenge of building an AWS platform from scratch to customize and integrate Cornerstone far beyond its out-of-the-box capabilities. What began as an adaptation layer and batch integrations has grown under this technical leadership into a distributed Java and Maven microservices architecture, event-driven workflows, standalone Next.js and Amplify applications, and applied AI solutions ranging from R&D agent pilots to client systems in production.
Technical leadership practiced from the inside: defining architecture and engineering standards (design patterns, SOLID principles, and unit, API, and UAT testing), supporting developers day to day, and continuing to write code directly while drawing on prior Project Manager experience so technical decisions stay aligned with project timelines and priorities.
Featured projects
Business need on the table, role in the project, and delivered solution.
01Integration / Present
Cornerstone customization and integration platform
- Context
- The starting point when joining evoluxia was clear: build an AWS platform from scratch to customize Cornerstone and connect it with payroll and other enterprise systems far beyond standard capabilities.
- Contribution
- Conception and construction of the platform from scratch: AWS architecture design for distributed Java and Maven microservices, shared libraries, and event-driven workflows, alongside development of core services, REST APIs, and Lambda integrations.
- Delivery
- Customization through JavaScript and Google Tag Manager, batch and event-driven pipelines distributing the employee golden record from Cornerstone, and evolution toward custom pages and full Next.js and Amplify applications.
- Impact
- Delivered a clear commercial differentiator as a Cornerstone partner and became the foundation on which standalone applications and AI solutions were later built.
Cornerstone / Java / Maven / Microservicios / Event-Driven / AWS Lambda / API Gateway / Google Tag Manager / Next.js / AWS Amplify
From platform customization to standalone applications
Evolution of a shared technical foundation
Platform conceived from scratch to expand technical reach as an implementation partner.
- 01
Customization
Cornerstone adaptation through JavaScript managed via Google Tag Manager.
- 02
Integration
AWS Lambda services, REST APIs, and batch processes using Cornerstone as the employee golden record.
- 03
Applications
Development of custom pages and Next.js applications on Amplify, both integrated and standalone.
- 04
Applied AI
Evolution toward proprietary AI solutions across client projects and R&D pilots.
02AI / Present
Enterprise AI agents platform
- Context
- Within evoluxia's R&D (I+D) line, a clear need emerged for a well-crafted proprietary product foundation adaptable to multiple AI use cases without rebuilding the architecture for every client.
- Contribution
- Conception and development of the complete core product, defining for each use case what objective the agent pursues, how it must respond, and which criteria pass internal UAT.
- Delivery
- Skills-configurable platform supporting interactive and background agents, scheduled or event-driven, connected to enterprise systems.
- Impact
- Pilots already presented to clients within the company's R&D (I+D) line, designed to evolve into a commercial product.
Next.js / Event-Driven / AWS Bedrock / AgentCore / MCP / Aurora PostgreSQL / CDK
AI agents tailored to each use case
- Customization
- Skills
- Behavior adaptable to each client's operational needs.
- Execution modes
- 2
- Interactive chat agents and autonomous background agents.
- Product stage
- R&D
- Pilots presented to clients within evoluxia's R&D (I+D) line.
- Internal validation
- UAT
- Goals and expected responses verified per use case.
From business goal to agent behavior
Complete core product, conceived and developed from scratch.
- 01
Objective
Definition of the problem the agent solves and the expected response.
- 02
Skills
Configuration of capabilities, rules, and enterprise connections required for the use case.
- 03
Execution
User conversation or background execution triggered on schedule or by events.
- 04
Internal UAT
Verification of agent behavior against the pilot's acceptance criteria.
03AI / Present
AI document and label comparator
- Context
- A client needed to eliminate manual character-by-character checks between versions of product labels and technical sheets without losing control over what went to print.
- Contribution
- Design and construction of the solution from scratch based on that client need, covering both OCR and AI extraction and the subsequent human validation workflow.
- Delivery
- Document comparison with OCR and AI, structured field-by-field differences, change history, and human review before approving any version.
- Impact
- The project is live in production.
Next.js / Amazon Textract / AWS Bedrock / Aurora PostgreSQL / AWS Amplify
Document comparison in production
From two document versions to a traceable review
Client solution built from scratch, always with final human validation.
- 01
Documents
Upload of the current product label or technical sheet and the new candidate version.
- 02
OCR & AI
Text extraction and structured comparison of the documentary content.
- 03
Differences
Field-by-field change detection and logging in the review audit trail.
- 04
Validation
Human review of the detected differences before approving changes.
04HR Tech / Present
Curriculum management, merit scoring, and AI validation
- Context
- The client project required an application capable of managing curricula and supporting documents, reviewing merits, and scoring candidates across selection calls without bottlenecking the team in manual checks.
- Contribution
- Conception and development of the complete application from scratch beyond the AI component: curriculum model, call configuration, scoring engine, integrations, and review inbox.
- Delivery
- Configurable CV by sections, fields, and profiles, merits with attachments, calls, rubrics, and rankings, alongside CVN import and enterprise system integration. AI compares the document against the declared merit using a configurable prompt and critical fields.
- Impact
- The similarity percentage guides the reviewer, but it is not a merit score or an accreditation guarantee. A person makes the final decision without AI accepting or rejecting anything on its own.
Next.js / Java / Maven / Microservicios / Aurora PostgreSQL / OCR / Document AI / AWS Bedrock / APIs HRIS
From curriculum management to AI-assisted document review
AI-assisted documentary evidence and final human decision
The similarity percentage supports the reviewer: it is not a merit score or an accreditation guarantee.
- 01
Configuration
Definition of the CV model, calls, scoring rubrics, prompt, and critical review fields.
- 02
Documentation
Registration of the declared merit together with its supporting document.
- 03
AI check
Document extraction, comparison against the declared merit, and similarity percentage calculation.
- 04
Human decision
Final human validation of the documentation, with scoring runs and candidate rankings.
05Custom software / Present
Personal training and health assistant
- Context
- The goal was to build an end-to-end personal training and health product, applying the same architecture rigor and care as a commercial SaaS platform.
- Contribution
- Complete design and build of the web application, native iOS and Apple Watch apps, data model, cloud sync, and visual identity.
- Delivery
- Session tracking, training load metrics, goals, notes, and contextual AI analysis, paired with an anonymous public demo featuring real workouts.
- Impact
- A live product in daily use whose public demo can be opened directly without login to explore anonymized real sessions.
Next.js / TypeScript / Supabase / Swift / iOS / HealthKit
Open live demo↗
Professional experience
April 2022 – Present
evoluxia
Tech Lead
The initial challenge at evoluxia was building the Cornerstone customization and integration platform on AWS from scratch and evolving it into Java and Maven microservices, event-driven architecture, and full Next.js and Amplify applications, both integrated with Cornerstone and standalone. The current role covers leading the development area: defining architecture and standards (SOLID), prioritizing with the team, testing strategy, and working directly in the code on applications and AI solutions.
- Coordination of engineering teams and management of scope, planning, and deliveries using sprints and Kanban tailored to each project.
- Definition of distributed Java (Maven) microservices architecture and event-driven workflows on AWS, applying design patterns, SOLID principles, and unit, API, and user acceptance testing (UAT).
- Conception and development of the core product for an R&D (I+D) AI agents platform, with pilots presented to clients and internal UAT per use case, plus a client document comparator in production.
- Design and development of SaaS products and B2B/B2E portals using Next.js, React, TypeScript, Tailwind CSS, and Java microservices with Maven.
- Distributed microservices architecture and event-driven workflows on AWS serverless (Lambda, API Gateway, S3, DynamoDB, Secrets Manager, Aurora PostgreSQL/RDS, Textract, Bedrock, and CDK), with deployments on Vercel and AWS.
- Definition of architecture standards, design patterns, and SOLID principles, shared Java libraries, and unit, API, and user acceptance testing (UAT).
- Development of well-crafted HR Tech solutions: curriculum evaluation, merit scoring, onboarding, training, document automation, and operational portals.
- Integration with Cornerstone, Microsoft SSO, Jira, InfoJobs, Sesame, Twilio/WhatsApp, Stripe, ERP/CRM, and REST APIs.
- Integration of generative AI and OCR into real business workflows using Bedrock, Gemini/Vertex AI, OpenAI, Textract/Document AI, NotebookLM, and MCP servers.
- Design of asynchronous jobs, ETL pipelines, Excel/PDF imports, validations, synchronizations, and data models for business-critical systems.
- Deployment coordination, secrets management, DEV/PRO environments, automation scripts, and cloud operations.
- Translation of business needs into clear technical solutions: analysis, architecture, implementation, and continuous product evolution.
Java 21/25 / Maven / Microservices / Event-Driven Architecture / SOLID / Unit & API Testing / Next.js 14/15/16 / React 18/19 / TypeScript / Tailwind CSS / PostgreSQL/Aurora / DynamoDB / AWS Lambda / API Gateway / S3 / Secrets Manager / Textract / Bedrock / CDK / Vercel / Docker / REST APIs / OAuth/SSO / OpenAI / Gemini/Vertex AI / MCP / NotebookLM / Make / Microsoft Copilot Studio
May 2014 – April 2022
atSistemas
DW-BI Project Manager
Leadership of data and BI projects with Qlik, PowerCenter, and Oracle ADF. Eight years as Data Project Manager at atSistemas, with the position carried out entirely at FC Barcelona.
- Coordination of technical teams and discovery sessions across departments to identify data silos and sources.
- Direct reporting to the IT Director of Data, with autonomy in decision-making and user acceptance testing (UAT) with key users. Project recognized with the CIONET Mejor Data Intelligence 2020 award.
- COR: technical management of the club's sports and medical management system.
- FCBme: project management of the mobility app for players and coaching staff.
- Corporate data warehouse: leadership of the unified platform for sports, commercial, and HR data.
- Definition of the data warehouse model and ETL processes feeding the analytical layer.
- Development of commercial and departmental dashboards (sports, medical, and HR) in Qlik Sense and QlikView.
- Qlik Sense administration and definition of Qlik development standards.
- Definition of data quality policies agreed and validated with internal departments.
- Project recognized with the Mejor Data Intelligence 2020 award (CIONET).
JDeveloper 11g y 12c / J2EE / Oracle ADF / Jira / Oracle / Webservices / Hybreed (movilidad) / QlikView / Qlik Sense / PowerCenter
January 2020 – September 2021
OBS Business School
Lecturer — Master in Big Data and Analytics
Teaching the Data Governance module in the Master in Big Data and Analytics.
- Instruction on data governance, data quality, and practical methodology for analytics professionals.
Data Governance / Big Data / Analytics
August 2008 – February 2014
Serhs Tourism
Project Manager
Full-cycle management of the hotel wholesaler platform: from hotel contracting and inventory loading to XML distribution of bookings and travel packages.
- 2008–2011: analysis and development of the wholesaler management portal in Oracle ADF and J2EE with dynamic forms.
- 2011–2014: project management, frontend team coordination, and systems architecture definition.
- Internal travel wholesaler operations and online hotel booking distribution.
JDeveloper 11g / Oracle / XSLT / J2EE / ADF / WebLogic / PowerDesigner
Skills and tools
AI in production
- AWS Bedrock (Converse, Agents, KB)
- OCR Textract / Document AI
- RAG / embeddings
- MCP servers
- OpenAI / ChatGPT (integration)
- Gemini / Vertex AI
- NotebookLM (workflow)
Engineering & cloud operations
- Next.js / React / TypeScript
- Java / Maven
- Microservices & Event-Driven Architecture
- AWS Lambda + API Gateway
- Aurora PostgreSQL
- DynamoDB
- Unit, API & UAT Testing
- CDK
- Vercel
- OAuth / SSO
Technical leadership
- Technical direction & active development in code
- Architecture, design patterns & SOLID
- Team mentoring & coaching
- End-to-end product delivery
- HR / ERP / SaaS integrations
Languages
English
Conversational, working proficiency.
Education
Higher VET Diploma (CFGS) in Business IT (Specialist Technician · FP II)
CE Vidal i Barraquer
1996 – 1999
Additional training
ThePower Business School
SAP All in One
