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About This Role
At Beam, you get to do work that matters for the world. We’re solving the world's toughest social problems with an incredible team, tech and AI. And we’re growing fast
It’s not easy. Nothing worth doing ever is.
Join a company at the forefront of social impact, driving first\-of\-its\-kind positive change. You’ll be part of a high\-performance culture where you'll make a huge impact, rapidly progress your career, and truly enjoy your work.
From top\-tier coaching and personal development budgets to competitive salaries, we take care of everyone who works at Beam.
We’ve already seen incredible growth from our Beam Notes product, helping frontline workers save over 8 hours of admin per week. From social workers and NHS clinicians to mental health practitioners and safeguarding specialists, nearly 100,000 frontline workers across the UK, US and Australia are now using Beam Notes regularly to deliver faster, more human\-centred support.
About the role
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As a Prompt Engineer at Beam, you'll be at the forefront of deploying our AI products into real\-world environments where they create meaningful social impact, and you'll do it in our fastest\-growing market.
Beam is transforming how social workers, case managers, clinicians and other frontline practitioners operate, freeing them from time\-consuming admin to focus on human\-centered support. The US expansion is where the next chapter gets written: state and local government agencies, home health and behavioral health providers, and care organizations that have never seen tooling like this.
You'll play a critical part in scaling that impact, working directly with US frontline practitioners to make sure our products are intuitive, effective and deeply embedded in their workflows. In this founding role you won’t be the one following a playbook, you’ll be writing it!
You'll be:
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You’ll work closely with frontline practitioners and internal teams to design, deploy and continuously improve AI\-powered templates and workflows.
Customer engagement and discovery
- Partnering with US frontline workers to understand their workflows, needs and challenges, including the documentation and reporting requirements specific to their state and program context
- Running discovery and review sessions to gather insights and refine solutions
- Owning customer usage, engagement and success metrics, ensuring strong outcomes and measurable impact
Template development and optimization
- Designing, building and testing high\-quality AI prompt templates using a range of LLM providers alongside agents such as Claude Code and Cursor
- Continuously iterating based on user feedback, internal reviews and performance metrics
- Ensuring outputs are accurate, compliant and tailored to real\-world use cases, including US regulatory and payer contexts such as Medicaid documentation standards
Tooling, automation and innovation
- Improving internal tools, automations and processes to scale template delivery and build the playbook for the US market
- Prototyping new ideas and features using AI coding tools
- Staying up to date with advancements in AI/LLMs and applying them to enhance product performance
Cross\-functional collaboration
- Working closely with Product, Engineering, Customer Success and Enablement teams across US and UK
- Contributing insights to the product roadmap and identifying opportunities for expansion and scaling in the US market
- Sharing learnings, documenting best practices and helping refine team processes
Data privacy and responsibility
- Maintaining a strong focus on data privacy, security and the ethical use of AI, including HIPAA\-level sensitivity where our products touch protected health information
- Ensuring all solutions are designed with care for the vulnerable populations Beam serves
You'll have:
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We're looking for someone who combines technical curiosity with a strong user focus and a passion for social impact.
Core attributes
- Strong and demonstrable interest in AI and prompt engineering, with a hands\-on, experimental mindset
- A proven ability to work on greenfield projects where you are building the process as you go rather than following a pre\-existing one
- User\-centric thinking that translates real\-world needs into practical, high\-quality solutions
- Creative problem\-solving, able to diagnose issues and iterate quickly
- High attention to detail, especially when working with nuanced or sensitive data
Ways of working
- Collaborative and comfortable working cross\-functionally with diverse teams, including colleagues in other time zones
- Proactive and ownership\-driven, with a focus on delivering measurable outcomes
- Adaptable and excited by fast\-paced, evolving environments
- Strong growth mindset with a desire to continuously learn and improve
Mission alignment
- Passion for social impact and improving outcomes for underserved communities
- Alignment with Beam's values: thoughtful, ambitious and deeply user\-focused
Nice to have
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- Experience or exposure to healthcare, behavioral health, home health, long\-term care or social services environments in the US
- Understanding of documentation, reporting or compliance workflows in frontline support settings, such as Medicaid billing documentation, EHR notes or case management records
Compensation:
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A base salary of $105,000 \- $145,000
*Final compensation will be determined based on the candidate's qualifications, skills, location and previous experience.*
Application process
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- A screening call with a member of the talent team
- A practical exercise reflecting real template and prompt work
- An interview with the hiring manager including a live presentation
- A final round interview with Beam's COO, Seb
*We are accepting rolling applications for this role, with no fixed close date.*
Perks
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- Healthcare plan
- 401k
- Access to therapy, coaching, classes and content, powered by Oliva
- Your own financial well\-being coach, through Bippit
- Generous holiday: 23 days, including 3 days over the Christmas period, plus US public holidays
- Eligible for a 6\-week sabbatical after 3 years in service
- Enhanced parental leave: Primary Caregiver leave is two weeks above the State minimum, and Secondary Caregiver leave is 2 weeks
- $270 WellBeam budget for activities enhancing wellbeing and professional development
- WFH equipment budget: up to $400 allowance to be used on workstation equipment (monitor, desk, keyboard, mouse, etc)
- Free subscription to the Calm meditation app
About Beam
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Our team of 200\+ embraces a hybrid working approach, enjoying 2\-3 days of vibrant collaboration in our beautiful Shoreditch co\-working space, fully equipped with rooftop views, an onsite barista and kitted out gym.
We’ve picked up an armful of awards for our work, including one from our former Queen. We've also been named by WIRED as one of London's 10 hottest startups and by LinkedIn as a Top 15 UK Startup. Meanwhile, we've been covered in the media literally thousands of times, including the likes of The FT, BBC, TechCrunch, Forbes and The Guardian.
We’re also proud to be backed by some of the world's leading tech investors and entrepreneurs, including the founders of Booking.com, Calm, Shazam and Dropbox.
Start your journey to a more impactful career today. We're excited to hear from you.
Reasonable adjustments:
Beam is committed to fostering an inclusive, diverse, and supportive work environment for all employees. This policy extends to our hiring practices.
We recognise that some candidates may need additional support during their hiring process to give them the best chance of being a success. To ensure that all candidates have an equitable opportunity during their process, we are committed to providing reasonable adjustments where required.
If you require a reasonable adjustment to be made during your process, please let your Talent Partner know. We encourage you to share this information, but there is no obligation to do so.
Please be reassured that any reasonable adjustment requests will not be taken into account when making a decision about your candidacy.
Compensation Range: $105K \- $145K
Role Details
About This Role
Prompt Engineers design, test, and optimize interactions with large language models. They build evaluation frameworks, craft system prompts, and develop techniques like chain-of-thought and few-shot learning to get consistent, reliable outputs. The role emerged alongside the GPT-3 era and has matured into a legitimate engineering discipline, not the 'just talk to the AI' job that early skeptics dismissed.
The work is more systematic than creative. You're running hundreds of prompt variations through evaluation suites, measuring output quality across edge cases, and building guardrails for production systems. When a prompt works 95% of the time but fails catastrophically on the other 5%, you need to find those failure modes and fix them before they hit users.
Across the 4,317 AI roles we're tracking, Prompt Engineer positions make up 0% of the market. At BEAM, this role fits into their broader AI and engineering organization.
Prompt engineering roles are still growing but the market is maturing. Early roles were broad and experimental. Now, companies know what they want: someone who can systematically improve LLM output quality, reduce costs by optimizing token usage, and build evaluation infrastructure. The roles that survive will be the ones that look more like engineering than copywriting.
What the Work Looks Like
A typical week involves designing evaluation datasets for new use cases, benchmarking prompt strategies against each other with statistical rigor, working with product teams to define 'good enough' output quality, and building the tooling that lets non-technical teammates iterate on prompts safely. You'll spend more time in spreadsheets and evaluation dashboards than you'd expect.
Prompt engineering roles are still growing but the market is maturing. Early roles were broad and experimental. Now, companies know what they want: someone who can systematically improve LLM output quality, reduce costs by optimizing token usage, and build evaluation infrastructure. The roles that survive will be the ones that look more like engineering than copywriting.
Skills Required
The core requirement is deep LLM experience: prompt design, RAG architectures, and evaluation methodology. Python is table stakes. Many roles also want experience with specific providers like OpenAI, Anthropic, or open-source models. Understanding tokenization, context windows, and the practical differences between model families (reasoning ability, instruction following, output format compliance) separates strong candidates from the crowd.
Evaluation skills are becoming the differentiator. Can you design a rubric that measures output quality? Can you build automated evaluation pipelines? Do you understand when to use human evaluation vs. LLM-as-judge vs. deterministic checks? Companies are moving past 'vibes-based' prompt testing and want engineers who bring measurement discipline.
Strong postings specify the LLM use cases (summarization, extraction, classification, generation), the evaluation methodology they expect, and the production environment. Weak postings just say 'prompt engineering experience' without context. Look for companies that mention evaluation frameworks and production deployment.
Compensation Benchmarks
Prompt Engineer roles pay a median of $145,000 based on 17 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($125K) sits 14% below the category median. Disclosed range: $105K to $145K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
BEAM AI Hiring
BEAM has 1 open AI role right now. They're hiring across Prompt Engineer. Based in New York, NY, US. Compensation range: $145K - $145K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into Prompt Engineer roles include Technical Writer, NLP Researcher, Software Engineer.
From here, career progression typically leads toward AI Product Manager, LLM Engineer, AI Solutions Architect.
The best prompt engineers come from technical backgrounds and add LLM expertise, not the other way around. If you're coming from a non-technical role, invest heavily in Python, evaluation methodology, and understanding how LLMs work under the hood (tokenization, attention, context windows). The role will increasingly merge with LLM Engineering as the tools mature.
What to Expect in Interviews
Interviews focus on evaluation methodology and systematic thinking. You'll likely be asked to design a prompt for a specific use case, explain how you'd measure output quality, and walk through how you'd debug a prompt that works 90% of the time but fails on edge cases. Expect to discuss tokenization, context window management, and the tradeoffs between different prompting strategies (few-shot vs. chain-of-thought vs. tool use).
When evaluating opportunities: Strong postings specify the LLM use cases (summarization, extraction, classification, generation), the evaluation methodology they expect, and the production environment. Weak postings just say 'prompt engineering experience' without context. Look for companies that mention evaluation frameworks and production deployment.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Prompt engineering roles are still growing but the market is maturing. Early roles were broad and experimental. Now, companies know what they want: someone who can systematically improve LLM output quality, reduce costs by optimizing token usage, and build evaluation infrastructure. The roles that survive will be the ones that look more like engineering than copywriting.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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