About this role.
Acquia is hiring a Staff AI Engineer for a hands-on individual-contributor role within its AI Core Engineering team. The role centers on designing, building, and operating production-grade, stateful multi-agent workflows for its enterprise digital experience platform. The engineer will use LangGraph, Temporal, Pydantic, and LangFuse while establishing standards for RAG, prompt management, evaluation, observability, reliability, and secure cloud deployment. This senior position also involves technical collaboration with product and platform teams, customer architecture discussions, and organic mentorship through design reviews, pairing, and high-quality code. Candidates need extensive software engineering experience, including at least three years delivering production AI agents.
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Cover letter sample
Dear Hiring Team,
I am excited to apply for the Staff AI Engineer role at Acquia. My background in Python, production LLM systems, agent orchestration, and cloud-native engineering aligns strongly with your need for reliable, observable enterprise AI workflows.
I would bring a hands-on approach to building LangGraph and Temporal-based agent systems, strengthening RAG and evaluation practices, and translating complex architecture into practical outcomes for product teams and customers. I am also motivated by the opportunity to mentor through thoughtful code reviews, pairing, and technical design leadership while helping Acquia advance its AI-powered DXP.
Thank you for your consideration; I would welcome the opportunity to discuss how I can contribute to Acquia's AI Core Engineering team.
Sample interview questions
I would model the workflow state explicitly with Pydantic schemas, define narrow agent responsibilities and tool contracts, and use LangGraph for conditional routing, cycles, and human-approval interrupts. I would use Temporal for durable execution, retries, timeout policies, idempotency, and recovery across long-running tasks. Each state transition would be traceable and tested against successful, failed, and partially completed execution paths.
I would instrument traces for every model call, retrieval action, tool invocation, and workflow transition, with appropriate redaction for sensitive data. I would version prompts, capture latency, cost, token use, model settings, and quality outcomes, then maintain representative evaluation datasets for regression testing. Dashboards and alerting would track reliability, failure modes, quality degradation, and cost anomalies by workflow and customer context.
I would first separate retrieval failures from generation failures by reviewing retrieved documents, chunking, metadata filters, ranking signals, and final citations. Improvements may include better document normalization, hybrid search, reranking, query rewriting, contextual chunking, and stricter grounding instructions. I would validate each change with an offline benchmark and production monitoring rather than relying on anecdotal results.
I would define a task-specific evaluation suite covering correctness, groundedness, tool-use reliability, latency, cost, safety, and structured-output adherence. I would run controlled comparisons using representative production-like inputs and assess operational concerns such as data handling, regional availability, rate limits, and fallback options. The final choice would balance measured quality with reliability, compliance, and total operating cost rather than selecting solely on benchmark scores.
I would make mentorship part of delivery by writing clear design documents, setting reusable engineering patterns, providing actionable code-review feedback, and pairing on high-risk technical work. I would explain tradeoffs and invite engineers to own well-scoped decisions, then support them with context and feedback. This approach raises team capability while preserving accountability and momentum on production outcomes.
About Acquia
Acquia empowers the world’s most ambitious brands to create digital customer experiences that matter. With open source Drupal at its core, the Acquia Digital Experience Platform (DXP) enables marketers, developers, and IT operations teams at thousands of global organizations to rapidly compose and deploy digital products and services that engage customers, enhance conversions, and help businesses stand out.
Headquartered in Boston, MA, Acquia is a Great Place to Work-CertifiedTM company, is listed as one of the world’s top software companies by The Software Report, and is positioned as a market leader by the analyst community. We are Acquia. We are building for the future and we want you to be a part of it!
Career Exploration at Acquia
Our recruitment process is designed to empower you in making the most informed decisions. Acquia is committed to providing an inclusive, transparent, efficient, and educational interview experience that cultivates exploration into career opportunities at Acquia
You will discover the opportunity to grow your career here and learn from a global team that empowers you to exceed boundaries and achieve the extraordinary.
Acquia is the digital experience platform built for a world where your audience isn’t only human. Its agents too.
As AI agents become active participants in how people discover, consume, and act on digital content, Acquia gives enterprise teams the platform to create, manage, and distribute experiences designed for both. Powered by agentic AI that orchestrates — not just advises — Acquia automates complex digital workflows within the governance guardrails large organizations require.
The world’s #1 Drupal hosting provider, Acquia brings together Content Management, Digital Asset Management, and Product Information Management in a single AI-powered Command Center: Acquia Source.
Acquia. Built for every audience, human or otherwise.
The Role: Acquia is seeking a Staff AI Engineer to join our AI Core Engineering team. This is first and foremost a hands-on engineering role — you will spend the majority of your time designing, building, and shipping production-grade agentic AI workflows across the Acquia DXP. LangGraph, Temporal, Pydantic and LangFuse are your primary tools; enterprise reliability, observability, and scale are your standards. You’ll also play a light but meaningful mentoring role, helping to lift the AI engineering capability of those around you as the team grows.
Key Responsibilities
- Write and ship production AI code daily — you are an active contributor.
- Architect agentic AI workflows using LangGraph, Temporal, Pydantic — stateful, multi-agent workflows built for enterprise scale and reliability.
- Own AI observability via LangFuse: tracing, prompt versioning, evaluation, and performance benchmarking across all model interactions.
- Set AI engineering standards for agent design patterns, RAG, prompt management, context optimization, and tool-calling strategies.
- Partner with product and platform teams to deliver AI architectures that meet enterprise SLA, security, and compliance requirements.
- Evaluate and adopt emerging tooling — benchmarking LLM providers, orchestration frameworks, and agentic stack improvements.
- Mentor engineers as a natural extension of your work — sharing knowledge through code reviews, pairing sessions, and design discussions, not through management overhead.
- Represent Acquia’s AI capabilities in customer architectural reviews, technical discovery, and roadmap conversations.
Required Experience
- 8+ years of software engineering with 3+ years in production of AI Agents.
- Hands-on LangGraph, Temporal, Pydantic expertise — stateful, cyclic, multi-agent workflows at enterprise scale.
- Hands-on LangFuse expertise – tracing, evaluation, prompt management, and dataset- driven testing
- Proficiency with agent harness frameworks such as LangChain or similar (e.g. LlamaIndex, CrewAI) — composing chains, tools, memory, and retrieval pipelines.
- Deep Python proficiency and strong engineering fundamentals (testing, CI/CD, architecture).
- Cloud AI deployment experience (AWS, Azure, or GCP) including containerization and inference cost management.
- RAG architecture knowledge— vector databases, embedding models, and retrieval strategies.
- B.S. in Computer Science or equivalent practical experience.
Desired Skills
- Enterprise SaaS or CMS, including familiarity with Acquia’s Drupal-based DXP experience
- Agentic development workflow fluency — AI-assisted coding tools (Copilot, Cursor, Claude) as everyday accelerators.
- Familiarity with persistent agent runtimes – such as OpenClaw and Hermes Agent, understanding cross-session memory, autonomous skill creation, and always-on agent infrastructure as it matures in enterprise contexts.
- LLM fine-tuning or model evaluation experience and awareness of foundational model tradeoffs.
- Human-in-the-loop — interrupt-driven agents and enterprise design
- Strong communication skills — able to present AI system design to both engineers and C-suite stakeholders.
- Senior IC track record — known for the quality of your own code and system designs, with mentoring that happens organically through great work, not through meetings.
We are an organization that embraces innovation and the potential of AI to enhance our processes and improve our work. We are always looking for individuals who are open to learning new technologies and collaborating with AI tools to achieve our goals.
Acquia is proud to provide best-in-class benefits to help our employees and their families maintain a healthy body and mind. Core Benefits include: competitive healthcare coverage, wellness programs, take it when you need it time off, parental leave, recognition programs, and much more!
Acquia is an equal opportunity (EEO) employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veterans status or any other protected status or characteristic under federal, state or local law unrelated to the ability to perform the job.
We are seeking an AI-Native candidate who treats AI not as an external tool, but as a fundamental extension of their cognitive workflow. The ideal candidate possesses an orchestration mindset—the ability to skillfully prompt, manage, and direct AI to navigate complexity—and maintains a high degree of AI fluency.
You should be characterized by radical adaptability and a “builder” mentality, showing a restless drive to transform traditional work processes into agentic workflows. Beyond technical proficiency, we value intellectual humility: the willingness to constantly unlearn old methods in favor of more efficient, AI-augmented processes. You don’t just use AI to do your job; you use it to redefine what your job can achieve.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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