The Mandate

Daemon helps enterprises ride technology waves, and AI assisted engineering is the current one. Everyone wants AI, but nobody has more engineers, and hiring cannot close the gap. We believe AI restructures engineering discipline rather than replacing it, shifting effort towards validation and assurance. Adopted naively, AI simply produces more code to review and quality risk rises with activity.

This role exists to make disciplined adoption real, inside Daemon and on client engagements. You will join for six months as a change agent, not a caretaker of the status quo. Your job is to shift how our consultants build software, measurably and permanently, then leave. Success means the capability outlives the contract, embedded in our people, patterns and delivery model.

You will work in lockstep with the Head of AI, building on the groundwork already laid: the Daemon harness - thin, model-agnostic primitives (skills, hooks, commands, rules) portable across the tools (Copilot, Claude) and clouds (AWS, Azure) our clients use - the L0-L4 capability ladder, the AI-SDLC handbook, and the partnership and case-study commitments that anchor Daemon's market credibility.

Success Criteria At Month Six

• 1. Technology baseline and development plans. A signed-off engineering technology standard - expected technologies, AI tooling and approved models - is published. 100% of engineers are baselined against it on the L0-L4 capability ladder, have an updated PDP in place, and show measured capability above L0, refreshed monthly.

• 2. Harness defined, trained and adopted. The harness is defined and published - thin, model-agnostic and portable across the tools and clouds our clients use. 100% of engineering consultants have passed the required training and certification as the prerequisite for access, and all have access and are using it where client requirements do not block it.

• 3. Partnership requirements, case studies and go-to-market. Partnership requirements are defined - including what "production" means and how historical projects qualify - and met, with a named, capable team delivering the partnership case studies by September. The use cases needed for credibility are defined with GTMs built from them, evidenced by four case studies (completed or in flight) including one public client reference strong enough to sell more work, and a priced, easy-to-buy AI-accelerated delivery proposition.

• 4. Engineering Centre of Excellence aligned and motivated. Every engineering Principal consultant has a calibrated 9-box assessment of company-goal alignment, engagement, delivery mindset and capability; anyone below expectation has a live SMART action plan, on track or complete. 100% of Principals, 70% of Seniors and 50% of Consultants are aligned or under a plan, with Principals demonstrably coaching their teams and contributing reusable patterns back to the harness.

The Six Month Arc

Phase	Months	Focus
Diagnose	1	Publish the engineering technology standard for sign-off. Baseline 1-00% of engineers against it on the L0-L4 ladder, alongside current tooling and velocity metrics.
Prove	2 - 3	Run focused pilots on live delivery work and demonstrate measurable throughput and quality gains. Publish the harness with its training and certification pathway, certifying pilot teams first. Ensure updated PDPs are in place for all consultants in the engineering CoE, starting with Principals and cascading down the grades. Stand up the named partnership case study team and begin the case studies so partnership commitments land by September. Begin 9-box calibration of Principals.
Scale	4 - 5	Roll the proven adoption model across all teams and certify remaining consultants so 100% hold hardness access and are using it where client requirements allow. Complete the four case studies (delivered or in flight) including the public client reference, and launch the priced AI-accelerated proposition with GTMs build from the use cases. Ensure that 9-box assessments are completed across the Center of Excellence with SMART action plans for anyone below expectation. Principals are coaching their teams and contributing patterns to the harness
Hand Over	6	Verify every success criterion: capability above L0 refreshed monthly, 100% certification case studies and proposition live, alignment thresholds (100% Principals, 70% Seniors, 50% Consultants) met or under a plan. Transfer ownership to named internal leads. Final report with quantified outcomes and a forward roadmap.

 

What You Will Do

Drive Adoption Across Delivery Teams

• Embed AI assisted engineering practices across Daemon delivery teams, working hands-on alongside consultants in live engagements.

• Apply the right pattern to each task using our L0-L4 capability ladder - Assisted, Augmented, Agentic and Autonomous - and the Daemon harness as the default toolkit.

• Coach engineers to reweight effort towards validation, security and assurance as AI takes on routine code production.

• Identify and remove the SDLC bottlenecks that AI adoption exposes, particularly in review and assurance capacity.

Build The Evidence Base

• Baseline throughput and quality on real work, then prove the gain with Flow and DORA metrics.

• Turn team-level results into reusable adoption playbooks, reference patterns and quantified ROI cases for client conversations.

• Contribute evidence towards the four AI-assisted engineering case studies (including one public client reference) and the partnership case-study requirements Daemon has committed to.

• Report progress to leadership monthly, with hard numbers rather than sentiment, and adjust the approach on evidence.

Change The Culture

• Win over sceptics through demonstration on their own work, not mandate - credibility is earned at the keyboard.

• Establish communities of practice, working agreements and standards that keep quality rising as throughput lifts.

• Support the Certification Bounty Programme and wider Enterprise AI strategy by lifting practical capability, not just credentials.

Leave The Capability Behind

• Design every intervention for the moment you are no longer needed - no dependency by design.

• Identify and develop internal champions who own the adoption model after the contract ends.

• Hand over a documented, working operating model with named owners, metrics and a forward roadmap.

Who You Are

You operate at the Managing Consultant level. You are known for domain expertise and capable of generating your own work and that of others. You explain complex technical ideas persuasively to technical and non-technical audiences at every level, up to the most senior. You understand the impact of emerging technologies on organisations and can analyse the risks of adopting or ignoring them.

Essential Experience

• Substantial hands-on software engineering background with recent, deep experience of AI assisted development in production environments.

• Practical fluency with modern AI coding tools and agentic workflows, including their failure modes and governance needs.

• A track record of leading engineering practice change across multiple teams, with measured results to show for it.

• Fluency with engineering performance measurement - DORA, Flow metrics and quality indicators - and using them to drive change.

• Consulting credibility - comfortable presenting to senior stakeholders and coaching engineers on the same day.

• Experience of enterprise or regulated delivery environments where assurance, audit and security are first-class concerns.

Desirable Experience

• Experience of spec-driven development, structured prompting practices or context engineering at team scale.

• Familiarity with staged AI adoption models and the governance needed to move teams up the capability ladder safely.

• Prior consultancy experience, or a role establishing an engineering enablement or developer productivity function.

• Contributions to engineering communities - talks, writing or open source - that demonstrate credibility as a practice leader.

About Daemon

Daemon Solutions is a UK technology consultancy. We help enterprises operationalise AI safely, at scale and in production. Our differentiator is discipline - validation, assurance and production rigour that survive each technology wave. We lift our clients’ own engineers rather than replacing them, and we design every engagement for the moment we are no longer needed. This role applies that same philosophy to ourselves.