Senior Applied AI Engineer

Gravitas Group; Manchester; Hybrid; GBP 65,000 - 80,000; Full time

Benefits offered by this job

Equity options

Hybrid working model

Healthcare benefits

Learning budget £500

25 days holidays

Job summary

Gravitas Group in Manchester is seeking a Senior Applied AI Engineer to own complex AI delivery within a consulting environment. You will design, build and deploy real‑world AI solutions, guiding projects from discovery to production while staying hands‑on with cutting‑edge technologies.

You will mentor engineers, shape technical direction and collaborate with clients to translate requirements into scalable, production‑grade systems using Python, ML and cloud platforms.

Qualifications

• > Strong experience building and deploying production‑grade Python applications.
• > Experience developing machine learning or generative AI solutions in commercial environments.
• > Hands‑on experience with LLMs, RAG architectures, Embeddings, Prompt engineering, Model evaluation, AI agents, Model serving and ML workflows.
• > Experience designing and delivering cloud‑native solutions on AWS, Azure or Google Cloud.
• > Knowledge of DevOps practices and Infrastructure‑as‑Code tooling.
• > Experience owning technical workstreams and making engineering decisions.
• > Strong understanding of software architecture and engineering best practices.
• > Agile software delivery experience.
• > Strong knowledge of Git, Linux/Unix, Docker, Open‑source AI, ML and MLOps tooling.
• > Excellent communication and stakeholder management skills.

Responsibilities

• > Own technical workstreams across the full project delivery lifecycle.
• > Work closely with clients to understand business challenges and define AI solutions.
• > Design, build and deploy scalable production‑grade AI systems.
• > Lead technical discussions, workshops, demos and discovery sessions.
• > Deliver high‑quality software engineering with strong testing, observability and documentation standards.
• > Collaborate with team leads and engineers on architecture and implementation planning.
• > Participate in sprint planning, retrospectives and code reviews.
• > Support and mentor other engineers across projects.
• > Help maintain engineering excellence and ensure outstanding client outcomes.
• > Keep pace with advancements in AI, machine learning and cloud technologies.

Skills

Python

Machine learning

LLMs

RAG

Embeddings

Prompt engineering

Model serving

AI agents

Git

Linux

Docker

Open‑source AI tools

Tools

AWS

Azure

Google Cloud

Kubernetes

Terraform

CI/CD

Job description

Senior Applied AI Engineer

Manchester (Hybrid - 3 days per week)
£65,000 - £80,000 + Equity + Benefits

Gravitas is proud to be partnering with a high-growth AI and technology consultancy as they continue to expand their industry-leading Applied AI and MLOps practice.

This is an exciting opportunity to join a business at the forefront of AI innovation, helping organisations across a diverse range of sectors design, build and deploy real-world AI solutions. Working across the full project lifecycle, you'll help customers turn complex challenges into scalable, production-ready systems using modern AI, machine learning and cloud technologies.

We're looking for an experienced engineer who enjoys combining strong software engineering expertise with applied AI, customer engagement and technical ownership.

The Opportunity

As a Senior Applied AI Engineer, you'll take ownership of complex technical workstreams while working closely with clients and delivery teams to build impactful AI solutions.

You'll play a key role in shaping technical direction, solving challenging engineering problems, mentoring colleagues and helping clients navigate their AI journey from discovery through to production deployment.

This position is ideal for an engineer who enjoys working in a consulting environment, thrives on solving real-world problems, and wants to remain hands‑on with cutting‑edge AI technologies.

You'll have the opportunity to:

• Deliver innovative AI and machine learning solutions for a wide range of clients
• Own technical workstreams from design through to deployment
• Work directly with customers to understand requirements and shape solutions
• Build production‑grade AI applications and platforms
• Mentor and support fellow engineers within delivery teams
• Influence architecture, delivery approaches and engineering best practices
• Contribute to thought leadership, R&D initiatives and technical content creation

What You'll Be Working On

Projects typically include:

• LLM-powered applications
• Retrieval Augmented Generation (RAG) systems
• AI agents and autonomous workflows
• Model serving and inference services
• Evaluation and monitoring frameworks
• Data engineering and AI pipelines
• Cloud-native infrastructure
• MLOps tooling and deployment platforms

You'll be responsible for delivering high-quality, secure and maintainable solutions while balancing customer needs, technical requirements and delivery objectives.

Key Responsibilities

• Own technical workstreams across the full project delivery lifecycle
• Work closely with clients to understand business challenges and define AI solutions
• Design, build and deploy scalable production‑grade AI systems
• Lead technical discussions, workshops, demos and discovery sessions
• Deliver high-quality software engineering with strong testing, observability and documentation standards
• Collaborate with team leads and engineers on architecture and implementation planning
• Participate in sprint planning, retrospectives and code reviews
• Support and mentor other engineers across projects
• Help maintain engineering excellence and ensure outstanding client outcomes
• Keep pace with advancements in AI, machine learning and cloud technologies

What We're Looking For

Essential Experience

• Strong experience building and deploying production‑grade Python applications
• Experience developing machine learning or generative AI solutions in commercial environments
• Hands‑on experience with technologies such as:
  • LLMs
  • RAG architectures
  • Embeddings
  • Prompt engineering
  • Model evaluation
  • AI agents
  • Model serving and ML workflows
• Experience designing and delivering cloud-native solutions on AWS, Azure or Google Cloud
• Knowledge of DevOps practices and Infrastructure-as-Code tooling
• Experience owning technical workstreams and making engineering decisions
• Strong understanding of software architecture and engineering best practices
• Agile software delivery experience
• Strong knowledge of:
  • Git
  • Linux/Unix
  • Docker
  • Open-source AI, ML and MLOps tooling
• Excellent communication and stakeholder management skills

Background

Applications are welcomed from individuals with backgrounds in:

• Software Engineering
• Machine Learning Engineering
• MLOps Engineering
• Data Science
• Platform Engineering
• DevOps Engineering

You don't need an existing Applied AI or MLOps title to be successful in this role. Strong engineering fundamentals, experience delivering complex software solutions and a passion for AI innovation are what matter most.

What's On Offer

• Salary of £65,000 - £80,000 depending on experience
• Equity options scheme
• Hybrid working model based in Manchester
• 25 days holiday, increasing to 30 days with service
• Enhanced maternity, paternity and adoption leave
• Healthcare cash plan
• £500 annual learning and development budget
• AI assistant subscription of your choice
• Cycle to Work scheme
• Volunteer and charity days
• Regular company socials and events
• Clear progression opportunities within a rapidly growing AI consultancy

Location & Eligibility

This is a hybrid role based in Manchester, with employees expected onsite three days per week (Monday, Wednesday and Thursday).

Occasional travel to customer sites across the UK may be required depending on project requirements.

Due to the nature of some client engagements, successful candidates must be eligible for UK Security Clearance (SC level). As a result, applicants should have been resident in the UK continuously for at least five years.