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For Companies At a Glance
- Tasks: Join us to build and enhance an AI-driven SaaS platform with backend feature work.
- Company: We're a boutique consultancy creating innovative AI solutions on AWS.
- Benefits: Enjoy remote work flexibility and competitive pay of $4,000-$6,000 for the project.
- Why this job: Be part of a cutting-edge project that combines AI and cloud technology in a collaborative environment.
- Qualifications: Proficiency in Python or Node.js, AWS stack experience, and familiarity with LLM APIs required.
- Other info: Opportunity for additional sprint projects after the initial build.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Project: 4- to 6-week build sprint
Location: Remote (2–3 h overlap with UK time)
Fee: Fixed-price USD $4,000-$6,000
About Us
We’re a boutique consultancy spinning up an AI-enabled SaaS product. Our AWS backbone—multi-AZ VPC, ECS Fargate, ALB, Terraform IaC, logging/monitoring, IAM hardening, etc. is already in place. Your brief is to layer business logic, API endpoints and a small admin UI on top of this platform, integrating an LLM-driven scoring pipeline plus a few external APIs.
What You’ll Tackle
- Backend feature work
- Design and ship REST or GraphQL endpoints.
- Build multi-tenant data models and role-based workflows.
- Trigger emails and webhooks for status changes.
- Wire existing prompts to an LLM API (OpenAI-compatible today, private model later).
- Store embeddings in a vector store and perform RAG look-ups.
- Surface “explanation” JSON for every model decision.
- Deploy new services into the existing Terraform / ECS stack—extend, don’t rewrite.
- Add CloudWatch alarms, log routes and parameter-store secrets where needed.
- Write unit and integration tests and set up a lightweight CI pipeline.
- Provide concise hand-over docs and 30 days of post-launch bug-fix cover.
Must-Have Skills
- Pro in Python (FastAPI) or Node.js (TypeScript / Nest)—ready to justify your pick.
- Experience extending an AWS stack (Terraform, ECS Fargate, ALB, Secrets Manager, KMS).
- Hands-on with LLM APIs and at least one vector database (Pinecone, Weaviate, OpenSearch, etc.).
- Multi-tenant data design with GDPR awareness.
- CI/CD and automated-testing mindset.
Nice-to-Haves
- Solution-architect background—ability to map future services and scaling paths.
- Prior LLM fine-tuning or custom-model training.
- Chrome-extension data capture.
- Transactional-email tooling (SES, Postmark, Mailgun).
Following this sprint project there will be an additional 2-3 sprint projects of similar size to follow.
Back End Developer employer: Future_find
Contact Detail:
Future_find Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Back End Developer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as FastAPI or Node.js with TypeScript. Being able to discuss your experience and preferences regarding these frameworks will show that you're not only qualified but also genuinely interested in the role.
✨Tip Number 2
Highlight any previous experience you have with AWS services, especially Terraform and ECS Fargate. Be prepared to share examples of how you've successfully extended an AWS stack in past projects, as this will demonstrate your capability to handle the technical requirements of the job.
✨Tip Number 3
If you have worked with LLM APIs or vector databases, make sure to mention specific projects where you implemented these technologies. Discussing your hands-on experience will help you stand out as a candidate who can hit the ground running.
✨Tip Number 4
Prepare to discuss your approach to CI/CD and automated testing. Sharing your mindset and strategies for ensuring quality in your code will resonate well with the team, as they value a strong focus on quality and operational excellence.
We think you need these skills to ace Back End Developer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python or Node.js, AWS stack, and LLM APIs. Use specific examples that demonstrate your skills in backend development and any relevant projects you've worked on.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in this specific project and how your skills align with the requirements. Mention your experience with multi-tenant data design and CI/CD practices to show you understand the role.
Showcase Relevant Projects: If you have previous work that relates to the job description, such as building REST or GraphQL endpoints or working with vector databases, include these in your application. Provide links to your GitHub or portfolio if possible.
Highlight Problem-Solving Skills: Since the role involves integrating an LLM-driven scoring pipeline, discuss any challenges you've faced in similar projects and how you overcame them. This will demonstrate your problem-solving abilities and readiness for the task.
How to prepare for a job interview at Future_find
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python (FastAPI) or Node.js (TypeScript/Nest). Highlight specific projects where you've implemented REST or GraphQL endpoints, and be ready to justify your choice of technology.
✨Demonstrate AWS Proficiency
Since the role involves extending an AWS stack, make sure to talk about your hands-on experience with Terraform, ECS Fargate, and other AWS services. Share examples of how you've deployed services and managed cloud resources effectively.
✨Discuss LLM and Vector Database Experience
Prepare to explain your familiarity with LLM APIs and vector databases. Discuss any relevant projects where you've integrated these technologies, and be ready to dive into the specifics of how you approached those challenges.
✨Emphasise Quality Assurance Mindset
Talk about your approach to writing unit and integration tests, as well as your experience with CI/CD pipelines. Providing examples of how you've ensured code quality and reliability in past projects will demonstrate your commitment to best practices.
