Distributed Cloud | Presales Engineer (Cloud, AI & Data)

Ever want to build mind-bending solutions that actually solve real problems Were looking for a Presales Engineer who can translate our data is a mess into heres how well fix it with some cloud magic and AI sprinkled on top.

Youll be the person who can fluently speak both nerdy tech and business reality without needing a translator. Youll design architectures demo them to customers who get excited (or look confusedyour job to bridge that gap) and then work with our delivery team to actually make it happen. Think of yourself as the bridge between whats theoretically cool and what actually works in production.
And youll use AI tools proficiently and wisely to build high-quality artifacts and proposals. We are AI-driven at our core and we make no apologies for it.

What Youll Actually Do

• Design and demo killer architectures Take customer pain points and sketch out solutions using GCP AWS Azure or hybrid setups that make your delivery team nod in approval

• Deep dive into their tech stack Understand their data pipelines AI needs cloud strategy and database nightmares (yes there will be vendor rants)

• Run technical workshops Explain why vector search is cool how multi-agent systems work and why they shouldnt just throw all their data into an LLM

• Collaborate with Sales Help identify what the customer really needs (hint: its usually not what they ask for initially)

• Prove it works Design and contribute hands-on to proofs-of-concept that actually validate feasibility not just pretty PowerPoint slides

• Bridge the gap Keep delivery teams in the loop early so there are no nasty surprises when implementation starts

• Keep things real Balance technical ambition with whats actually achievable given budget time and the customers existing tech debt

A Day in the Life of a Presales  Engineer at Devoteam Portugal

Your day wont be anything like this to be honest but you can get an idea of the activities our Presales engineers typically go through in their day-to-day work. Some are more frequent than others.
 

08:45 Morning Coffee & Work organization with the team
You roll in (remotely or at our office) and catch up with the team. Theres a question about whether Vertex AI or SageMaker is better for a customer use case. You jump into the thread with nuanceit depends. You discuss and share the pain of having too many engagements at once. This is sometimes a very fast-paced job. 

10:00 Deep Dive Call with the Customer
Youre on a call with a financial services customer drowning in batch data processing. Their current ETL is held together by SQL prayers and scheduled tasks. You ask probing questions: Whats your data volume Latency requirements Budget for cloud migration Youre taking mental notes on architecture patterns that might fit.

11:30 Whiteboard Time (Virtual or Physical)
Back at the office (or in ) youre sketching out a solution architecture. They need real-time data streaming for risk analysis so youre designing a data mesh approach with Solace BigQuery and maybe some agentic AI for anomaly detection. You snap a photo of the whiteboard and send it to the team chat.

12:30 Lunch Async Context Dump
You document your thoughts on the opportunity in Jira and a draft slide presentation. You involve the area lead: Hey we have this situation and from what we discussed before I think this is a possible solution for it but Im worried about the total effort vs the customer benefit. Any thoughts on your side

14:00 Sales Enablement Sprint
The sales team has a prospect call at 15:30. They want you to join and handle the technical architecture discussion. You prep a simple (but not too simple) slide deck showing cloud options without overcomplicating it.

15:30 Prospect Call
You present three architecture patterns for their AI-powered recommendation engine. One is cloud-native (cool but pricey) one is hybrid (balanced) one is mostly on-prem with cloud augmentation (safe boring). The prospect gets genuinely interested in option 2. You book a follow-up technical workshop.

16:45 PoC Validation Check
Youre overseeing/building a proof-of-concept for another customer (Python SQL vector embeddings the works). You review the technical approach with the delivery team and get the approval for the next phase.

17:15 Proposal Dry-run and Validation
45-minute team meeting presenting and improving the proposals that need to be delivered in the next couple of days. A bit like Shark Tank with your team mates to get the proposal. Occasionally you discuss specific technical challenges about the problems and solutions proposed coming from last weeks customer call: Turns out they cant shard their database. We need a Plan B.

17:45 Catch-Up & Tomorrows Prep
You wrap up email prep for tomorrows customer demo review some new AI/ML research that might be relevant and update your solution library with that neat architecture pattern you learned from the financial services call.

Qualifications :

The Non-Negotiables:

• You can build PoCs not just slides Youre able to spin up small applications and proofs-of-concept that actually run and prove value to the customer whether youre writing the code yourself or orchestrating AI code assistants to do the heavy lifting

• Cloud is your playground Youre comfortable with at least one of GCP AWS or Azure and you know how to stitch managed services together into something that works reliably in the real world

• You speak Data AI & Modern Apps fluently You should have real experience with at least 2-3 of these:

  • Machine Learning You understand supervised/unsupervised learning have worked with real models and know when ML is overkill

  • Natural Language Processing Transformers embeddings RAG prompt engineeringyouve actually used them in projects not just in blog posts

  • Computer Vision Image classification object detection you know the fundamentals

  • Generative AI Youve experimented with LLMs fine-tuning multi-agent systems vector search and you know the difference between a cool demo and something that can survive production

  • Application Modernization Youve seen legacy apps up close helped refactor or replatform them and understand patterns like strangler fig decomposing monoliths and moving toward microservices or modular architectures

  • Cloud-Native Migrations Youve been involved in moving workloads to cloud-native architectures (containers serverless managed databases) and understand the trade-offs and migration paths

  • Data Streaming Kafka or similar event-driven systems real-time processingyou know why and when streaming matters

  • Data Modelling Youve worked with Kimball Data Vault or modern approaches and you know when to denormalize and when not to

• Databases are not a mystery You understand the basics of OLTP vs OLAP have worked with at least a couple of real database engines and can reason about performance and fit at a high level

• You get how customers buy tech You understand that PoCs pilots and architecture reviews are part of a buying journey and you know how to keep both the CTO and the engineering team on board.

• Bachelors degree in Computer Science AI Data or related field (or equivalent demonstrable experience that makes us ignore the degree requirement)

• Customer presence: Sometimes we need to be in person with customers to present our cool ideas and solutions. And its great to have direct feedback at the table so its expected that youre willing to do some light travelling in Portugal mainly around the offices areas (Lisboa Porto Aveiro)

Nice-to-Haves:

• At least 6 months of hands-on experience using AI code assistance accelerators like Gemini Code Assist Claude Code Cursor Windsurf or similar tools and youre comfortable working with coding-focused LLMs such as Gemini Claude Sonnet/Opus or OpenAI-style code models to accelerate PoCs and solution experiments

• 6 years building real AI or data projects with some architecture responsibility

• Masters or PhD in a relevant field (but this wont make up for lack of practical experience)

• Infrastructure-as-code (Terraform CloudFormation) and cloud governance (FinOps IAM)

• Docker and Kubernetesyou know containerization is more than it works on my machine

• Youve presented to C-suite or board-level stakeholders without flinching

• Youve actually failed at something ambitious and learned from it

Additional Information :

What Devoteam Portugal Offers

• Work on genuinely interesting problems Not cookie-cutter consulting; we handle complex end-to-end transformations in data AI and cloud

• Room to grow Directors architects specialistswe promote from within when youre ready

• Portugal vibes Were based in Portugal and proud of it: great weather great food and a growing tech scene. We work flexibly and remotely but we genuinely like to meet up in personoffice days team days meetups and the occasional after-work drink are part of how we stay connected as a team

• Tools & learning budget We invest in your growth. Take courses attend conferences experiment with new tech

• Collaboration over hierarchy Were lean and mean. Youll talk directly to decision-makers not through three layers of management

• Flexibility Remote work flexible hours and we actually trust you to get the job done

• Performance-related Compensation - part of your compensation is directly tied to your performance with conversion ratios and influenced revenue playing an important part. The better you are the more you make!

The Devoteam Group works for equal opportunities promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.

Remote Work :

No

Employment Type :

Full-time