Company Description
OpenAsset is the leading marketing platform for the Architecture, Construction, and Engineering industries, trusted by 1,000+ clients over 20 years. Our mission is to be the most innovative partner to AEC firms, delivering solutions that help win more projects.
Last year we launched Shred.ai – world‑leading AI product for AEC marketers to help them speed‑up manual and repetitive tasks of analysing (‘shredding’) RFPs and drafting high‑quality compliant proposals grounded in the rich organisational knowledge of their firms.
We’re a diverse, collaborative, and fast‑growing team of 100+ employees with offices in New York and London and a global client base. Backed by Marlin Equity Partners, we’re passionate about creating an inclusive workplace where everyone feels valued and has a voice, and we actively hire from a diverse pool of candidates.
Description
Embark on an exciting journey as a Staff Software Engineer – AI/ML at OpenAsset, where you’ll play a pivotal role in shaping the future of AI/ML within our organization and AI‑enabled products we’re building to support the AEC industry. In this hands‑on technical role, you’ll not only drive the development of innovative machine learning models and AI‑driven solutions, leveraging frontier LLM models, agentic AI frameworks, model serving infrastructure, MLOps, LLMOps and AgentOps, agentic coding orchestration tools such as Claude Code, platforms including AWS, Amazon Bedrock, and Google GCP Vertex AI, but also strengthen the AI/ML competency at OpenAsset.
You’ll help establish the team’s strategic vision, processes, and best practices. You’ll design and implement scalable, efficient, and maintainable AI/ML systems while setting the standard for excellence in model deployment, data pipeline optimisation, and agentic AI applications. Beyond writing exceptional code, your leadership will be key in building a high‑performing team, mentoring engineers, and tackling complex technical challenges.
If you’re passionate about AI and how to build AI‑based products for customers, building products from the ground up, and delivering impactful solutions, we invite you to take on this foundational role. Join us to make a lasting impact on our products, our people, and the future of AI/ML at OpenAsset.
Responsibilities
As a Staff Software Engineer – AI/ML, MLOps/DevOps, your day‑to‑day activities will center on technical leadership, effective communication, and a hands‑on approach to delivering innovative AI/ML solutions. You’ll play a key role in shaping the success of the AI/ML team and driving impactful outcomes for the company.
Project Ownership
- Lead the design, planning, estimation, and coordination of AI/ML initiatives across multiple releases, including information extraction, model development, model serving, model training, data pipelines, and deployment.
- Take ownership of the entire lifecycle of AI/ML systems, from experimentation to production, ensuring timely and high‑quality delivery.
Cross‑Team Collaboration
- Partner with Product and Engineering teams to integrate AI/ML capabilities into company‑wide projects, addressing cross‑functional challenges.
- Collaborate with Product, Engineering, DevOps, and other teams to ensure seamless data flow, model deployment, and system integration.
Technical Leadership
- Provide strategic technical guidance on MLOps frameworks and practices, tools, and best practices that align with the company’s goals.
- Research and propose advanced machine learning techniques and cloud‑native AI services, including LLMs, MLOps and DevOps platforms, training and evals frameworks, and Amazon Bedrock, to enhance our capabilities.
Communication and Mentorship
- Foster a collaborative environment by communicating effectively across technical and non‑technical teams.
- Mentor and guide team members through agentic coding practices, code reviews, technical coaching, and knowledge sharing, building a culture of continuous learning.
Strategic Problem Solving
- Proactively identify challenges in AI/ML workflows and propose innovative, scalable solutions.
- Define and refine methods and procedures to optimise model performance, system efficiency, and team productivity.
Model Performance, Reliability, and Compliance
- Drive initiatives to improve model accuracy, scalability, and reliability while adhering to privacy, security, and compliance standards.
- Take a leading role in addressing issues related to data quality, bias mitigation, and model interpretability with minimal oversight.
Documentation and Knowledge Sharing
- Ensure comprehensive documentation of models, pipelines, algorithms, and system architecture to support team‑wide knowledge sharing.
- Maintain and enhance AI/ML playbooks and best practices to streamline onboarding and continuous improvement.
Skills and Experience
- 7+ years of experience in AI/ML engineering, including MLOps, AI infrastructure, building, deploying and maintaining machine learning models in production environments.
- 3+ years of technical leadership experience, with a track record of guiding teams through complex AI/ML projects.
- Expert proficiency in programming languages such as Python, Java or Rust, and Infrastructure‑as‑Code with focus on MLOps, AI infrastructure design and implementation, data engineering, pipelines automation, machine learning, models evaluation and support of live production AI systems.
- Deep understanding of AI/ML systems architecture, including experience with distributed systems and large‑scale data pipelines.
- Strong expertise in deploying and managing AI/ML models in cloud environments, with hands‑on experience using AWS services such as Amazon Bedrock, SageMaker, and related tools, or alternatives in GCP (Vertex AI) or Azure (AI Studio) cloud.
- In‑depth knowledge of model serving infrastructure, machine learning algorithms and frameworks, including experience with LLMs, AI agentic patterns, and fine‑tuning pre‑trained models.
- Experience with microservices architecture and CI/CD pipelines / MLOps for AI/ML model deployment, ensuring scalability, reusability, and testability.
- Experience with agentic AI coding and orchestration tools for software engineering, such as Claude Code, Codex, or similar.
- Proven ability to mentor and guide engineers, fostering growth and technical excellence without formal direct reporting relationships.
- Strong collaboration skills, working cross‑functionally with Engineering, DevOps, and Product teams to deliver impactful AI/ML solutions.
- Experience with Agile/Scrum methodologies, effectively managing sprints and delivering iterative improvements.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
Technologies we use
- Python, Rust, Java
- AWS, Amazon Bedrock, SageMaker, Vertex AI
- Datadog, Databricks, MLFlow, Grafana, OTel
- Agent SDK, LangGraph, LangFuse, Pydantic AI
- Claude, Gemini, ChatGPT, open‑weight LLM models
- Terraform, Docker, Kubernetes
- RMDBs, Graph DBs, Vector DBs
- Claude Code
- GitHub (and GitHub Actions)
Benefits
- Competitive salary
- 25 paid vacation days
- 8 bank holidays
- 5 paid sick days
- SSP
- Work from home flexibility
- Paid parental leave
- Pension programme
- Bike storage/shower facilities in building
- Career growth and development opportunities
This position is not eligible for visa sponsorship.
Axomic is an Equal Opportunity Employer. We base our employment decisions entirely on business needs, job requirements, and qualifications—we do not discriminate based on race, gender, religion, health, parental status, personal beliefs, veteran status, age, or any other status. We have zero tolerance for any kind of discrimination, and we are looking for candidates who share those values. Applications from women and members of underrepresented minority groups are welcomed.
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