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About This Role
Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We’re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.
Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.
Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We’ve built a product customers love and a business that’s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines.
At Aircall, you’ll join a company in motion. We’re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.
How we work at Aircall: We’re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you’ll feel at home here.
This role sits within GTM Enablement, part of the broader Customer Solutions & Applied AI organisation responsible for turning Aircall's AI Voice Agent (AIVA) and AI Messaging Agent (AIMA) into adopted, well-understood products across the business. GTM Enablement works alongside Forward Deployed Engineering, Solutions Engineering, Customer Engineering, Product Support, and Number Operations, globally across EMEA, AMER, and APAC. This is a new, dedicated enablement role created to keep the field current on AIVA and AIMA as they evolve, working in particularly close partnership with Forward Deployed Engineering and with the Product and Engineering teams shipping the roadmap.
As Product Enablement Manager, you will own how the field learns about every new AI Agent capability, use case, and release. This is a jack-of-all-trades, full-stack role: you need to be technical enough to understand agentic concepts such as intents, prompts, guardrails, and evals, creative enough to turn them into content people actually engage with, and comfortable producing that content yourself end to end, from writing through to filming and editing video. You'll work hand in hand with Forward Deployed Engineering to understand what the field actually needs, and directly with Product and Engineering to get ahead of what's shipping next. You are expected to be AI-first in how you work, using AI and agentic tooling to write, edit, and produce content at a scale a traditional enablement function could not, and to find agentic ways to enable the organisation more broadly, not only through content.
Core Responsibilities
- Own internal and customer enablement for every new AIVA and AIMA launch, translating roadmap items and release notes into playbooks, one-pagers, and videos for Forward Deployed Engineering, Solutions Engineering, Customer Engineering, Product Support, and GTM.
- Produce video as a default enablement format: script, record, and edit feature walkthroughs, demo videos, and "what changed and why it matters" explainers.
- Operate AI-first across the full content workflow, using AI tools to draft scripts, generate and edit video and audio, translate and localise content, and repurpose one asset into multiple formats.
- Build agentic tools and workflows that enable the organisation beyond content, such as internal agents that let teams self-serve answers or auto-generate first drafts of documentation.
- Work in lockstep with Forward Deployed Engineering to understand field pain points and priorities, and directly with Product and Engineering to get early visibility into what's shipping, so every release ships with an enablement plan ready to go.
- Build reusable frameworks, templates, and video formats that make each subsequent launch faster to enable than the last.
- Run live sessions, such as launch briefings or office hours, where they are the right tool, while defaulting to scalable, on-demand content wherever possible.
- Maintain a single, current source of truth for AIVA/AIMA product knowledge across the internal knowledge base or external customer LMS.
- Track enablement effectiveness, including content usage, time-to-competency on new features, and internal Q&A volume, and use that data to prioritise what to build next.
- Feed field questions, confusion points, and gaps back to Product and PMM so future releases ship with enablement already built in.
Qualifications:
- 2–4+ years of experience in product enablement, technical writing, solutions engineering, forward deployed engineering, content/product marketing, or a similar hybrid role at a SaaS or AI/platform company. Candidates without a formal enablement title are welcome if the underlying skills below are there.
- Technical fluency: comfortable with agentic AI concepts (prompting, intents, guardrails, evaluation) and able to hold a credible technical conversation with Product and Engineering without a translator.
- Full-stack content skills: strong written communication, plus the hands-on ability to script, shoot, and edit video end to end, not just brief a production team.
- AI-native operator: you use AI tools fluently for writing, video and audio generation, editing, and content repurposing, and can build simple agentic tools or workflows rather than only using AI as an assistant.
- Proven ability to build something from scratch in a fast-moving environment with minimal structure, team, or budget.
- Strong stakeholder management across Product, Engineering, Forward Deployed Engineering, and GTM Enablement.
- Analytical mindset, with experience defining and tracking content or enablement effectiveness (usage, time-to-competency, adoption).
Nice to haves
- Experience at a high-growth AI Companies or developer tooling products
- Background in contact centre technology or agentic technology
- Hands-on experience with AI video/audio tools (e.g. Descript, CapCut, Runway, ElevenLabs, Synthesia, HeyGen).
- Experience building lightweight agentic workflows or automations (e.g. Zapier, Make, n8n).
- Prior experience in a formal product enablement, sales enablement, or technical training role.
Base salary range:
$94,500 - $110,500 USD
Why join us?
Key moment to join Aircall in terms of growth and opportunities
* ️ Our people matter, work-life balance is important at Aircall
Fast-learning environment, entrepreneurial and strong team spirit
45+ Nationalities: cosmopolite & multi-cultural mindset
Competitive salary package & benefits
DE&I Statement:
At Aircall, we believe diversity, equity and inclusion – irrespective of origins, identity, background and orientations – are core to our journey.
We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We’re working to create a place filled with diverse people who can enrich and learn from one another. We’re committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.
We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.
Want to know more about candidate privacy? Find our Candidate Privacy Notice
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $94K-$110K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $178K across 36 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 11,520 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Aircall, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $215,000 based on 212 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($102K) sits 52% below the category median. Disclosed range: $94K to $110K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Aircall AI Hiring
Aircall has 8 open AI roles right now. They're hiring across AI Agent Developer, AI/ML Engineer, Data Scientist. Positions span New York, NY, US, Sydney, New South Wales, Australia, New York, NY. Compensation range: $110K - $110K.
Location Context
AI roles in New York pay a median of $221,000 across 3,257 tracked positions. That's 4% above the national median.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 median, while Prompt Engineer roles sit at $140,000. 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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