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Senior Software Engineer
TechTree's client
Salary
Undisclosed
Work mode
On-site
What we're looking for
- 4–6 years building production-grade systems
- Strong full stack capability
- Hands-on experience with modern LLMs, agents, embeddings
- Track record of integrating AI into business processes
- Comfort with data-intensive systems (Kafka, Spark, Databricks)
About the role
The role
A startup-shaped role embedded with the internal team. You will see how workflows actually run across the business, find the bottlenecks, and build tools that fit the way the company operates. Internal MVPs land on your desk and you take them from zero to enterprise-ready, with the codebase hygiene to make sure the second version doesn't fall over.
The skillset shape is forward-deployed — technical judgement, proximity to the business, and pace.
What you'll own
Architecture and end-to-end delivery of internal systems, taking MVPs through to production-grade applications
The cloud infrastructure footprint — environments, deployment pipelines, observability, cost
Security and GDPR compliance across the stack
AI workflows integrated into real business processes across investment, planning, delivery and operations
Codebase hygiene — Git practice, code review, repo structure, documentation
What we're looking for
Engineering and AI:
4–6 years building production-grade systems, ideally at a high-quality startup
Strong full-stack capability across SQL, backend services and a modern frontend framework
Real ownership of architectural decisions in production, including the trade-offs that come with distributed systems and scale
Hands-on experience building with modern LLMs, agents, and embeddings
Track record of integrating AI into real business processes, not just experimentation
Working understanding of AI evaluation, safety constraints and failure modes
Infrastructure and craft:
Comfort with data-intensive systems — ingestion, processing, storage (Kafka, Spark, Databricks or equivalent)
Cloud fluency on AWS, Azure or GCP · infrastructure-as-code (Terraform, Bicep, CDK or equivalent) · CI/CD · Docker (Kubernetes a bonus)
Fluent in Git, API design (REST/GraphQL), and security as a default consideration
Mindset:
Demonstrable history of taking products from zero to production to iteration
Strong problem-solving — you can translate ambiguous business problems into clean technical solutions
Comfortable in fast-moving environments with limited scaffolding
Genuine interest in the frontier of what AI can do, and a view on what's hype versus what's useful
Why join
The first proper engineering seat at a £3bn real estate platform with a serious growth pipeline
No inherited tech debt, no committees, no organisational drag — direct partnership with senior management on shaping the technology agenda
Real proximity to the business — investment, development, planning and operations are all in the building and part of your workflows
Competitive compensation
Central London office, in-person
A startup-shaped role embedded with the internal team. You will see how workflows actually run across the business, find the bottlenecks, and build tools that fit the way the company operates. Internal MVPs land on your desk and you take them from zero to enterprise-ready, with the codebase hygiene to make sure the second version doesn't fall over.
The skillset shape is forward-deployed — technical judgement, proximity to the business, and pace.
What you'll own
Architecture and end-to-end delivery of internal systems, taking MVPs through to production-grade applications
The cloud infrastructure footprint — environments, deployment pipelines, observability, cost
Security and GDPR compliance across the stack
AI workflows integrated into real business processes across investment, planning, delivery and operations
Codebase hygiene — Git practice, code review, repo structure, documentation
What we're looking for
Engineering and AI:
4–6 years building production-grade systems, ideally at a high-quality startup
Strong full-stack capability across SQL, backend services and a modern frontend framework
Real ownership of architectural decisions in production, including the trade-offs that come with distributed systems and scale
Hands-on experience building with modern LLMs, agents, and embeddings
Track record of integrating AI into real business processes, not just experimentation
Working understanding of AI evaluation, safety constraints and failure modes
Infrastructure and craft:
Comfort with data-intensive systems — ingestion, processing, storage (Kafka, Spark, Databricks or equivalent)
Cloud fluency on AWS, Azure or GCP · infrastructure-as-code (Terraform, Bicep, CDK or equivalent) · CI/CD · Docker (Kubernetes a bonus)
Fluent in Git, API design (REST/GraphQL), and security as a default consideration
Mindset:
Demonstrable history of taking products from zero to production to iteration
Strong problem-solving — you can translate ambiguous business problems into clean technical solutions
Comfortable in fast-moving environments with limited scaffolding
Genuine interest in the frontier of what AI can do, and a view on what's hype versus what's useful
Why join
The first proper engineering seat at a £3bn real estate platform with a serious growth pipeline
No inherited tech debt, no committees, no organisational drag — direct partnership with senior management on shaping the technology agenda
Real proximity to the business — investment, development, planning and operations are all in the building and part of your workflows
Competitive compensation
Central London office, in-person
Compensation & benefits
Salary: Undisclosed
About TechTree's client
This organization is a family-owned real estate developer, owner and operator specialising in hotels and student housing in Central London. £3bn portfolio, 4.0 million sq ft delivered. We invest our own equity, control delivery end-to-end, and operate what we build — from The Dixon and Lost Property in London to Courtyard by Marriott in Oxford, and the recent signing of The Derby London City with Hilton. We are now investing in the technology foundation that will let us scale faster across investment, development, planning and operations.