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Senior Forward Deployed Engineer (AI Agent)

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Remote from
Australia
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
12 Nov 2026
Listing views
17
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AI Summary

The role, at a glance.

Cresta is seeking a Senior Forward Deployed Engineer to build, deploy, and optimize enterprise AI agents using LLMs and agent frameworks. The role combines hands-on software engineering, customer-facing solution delivery, systems integration, and technical project coordination. Core work includes integrating APIs, CRMs, databases, and data pipelines; improving prompts and agent configurations; and troubleshooting production deployments. The engineer will partner closely with customers, product managers, ML engineers, and software engineers to turn deployment learnings into scalable platform improvements. Success requires strong Python and Golang skills, cloud and DevOps experience, AI-agent architecture knowledge, and clear stakeholder communication.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a technically demanding customer-facing engineering role requiring production AI-agent development, enterprise integration expertise, and the ability to translate ambiguous business requirements into reliable solutions. The engineer must balance rapid iteration with security, scalability, performance, and delivery commitments across multiple stakeholders.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$165,000
US market range$135k–$205k
AI insightNo numeric salary range is disclosed, so these figures are estimated for the US market in USD. For a senior forward deployed AI engineer with LLM, cloud integration, and enterprise customer-delivery responsibilities, a typical estimated base-salary market range is $135,000 to $205,000 annually, with an estimated midpoint of $165,000; equity and benefits may be additional.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe an AI-agent solution you deployed for a real business workflow. How did you define success and evaluate its performance?

I would begin by identifying the user journey, failure modes, integration requirements, and measurable outcomes such as containment rate, task completion, latency, accuracy, or escalation rate. I would deploy incrementally, establish baseline metrics, use representative test cases and A/B experiments where possible, and combine quantitative monitoring with customer feedback to prioritize improvements.

How would you design an AI agent that needs to retrieve account information from a CRM and take an action in an external system?

I would define tightly scoped tools for CRM retrieval and the external action, with validated schemas, least-privilege credentials, authentication, audit logging, rate limits, retries, and clear confirmation requirements for consequential actions. The agent would use retrieval only for relevant context, validate inputs and tool outputs, and fall back to human review when confidence, policy, or authorization checks fail.

What is your approach to improving an underperforming RAG-based agent?

I would first separate retrieval problems from generation and workflow problems by inspecting queries, retrieved documents, rankings, citations, and final responses. I would improve document chunking and metadata, tune retrieval and reranking, strengthen grounding instructions, add evaluation datasets, and monitor task-level metrics before making controlled changes.

How do you manage technical delivery when customer requirements are ambiguous or change during an implementation?

I translate broad goals into a written problem statement, assumptions, milestones, acceptance criteria, risks, and a prioritized backlog. I validate the highest-risk assumptions early through a prototype or demo, maintain frequent stakeholder updates, document decisions, and clearly communicate delivery tradeoffs when scope changes.

How would you troubleshoot a production AI-agent integration that intermittently fails for enterprise users?

I would use correlation IDs and observability data to trace requests across the agent, tool calls, APIs, and downstream services. I would examine authentication expiry, rate limiting, payload validation, timeout behavior, data quality, and retry patterns, then reproduce the issue in a safe environment and implement a monitored fix with an appropriate fallback path.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.

Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu, founded and led Google’s Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.

Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.

About the role:

At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.

As an AI Agent Engineer, you’ll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.. This position requires strong engineering skills, adaptability, and customer engagement. If you are self-driven, analytical, and eager to leverage AI in practical applications, this role is for you.

What You’ll Do :

  • AI Agent Development: Develop, configure, deploy, and optimize AI agents using Cresta’s AI platform and tools.
  • System Integration: Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration.
  • Performance Optimization: Optimize AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments.
  • Requirements Gathering: Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions.
  • Demos & Iteration: Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives.
  • Project Coordination: Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams — identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings.
  • Partner Cross-Functionally: Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximize customer ROI.
  • Technical Guidance: Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. Provide technical guidance on AI agent best practices, including architecture design, security considerations, and scalability planning.

What We’re Looking For:

  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Experience: 3+ years of full-time working experience in software development/Consulting, AI/ML engineering, or Forward Deployed Engineering.
  • Programming Skills: Proficiency in Python and Golang, with the ability to write clean, efficient code.
  • AI/ML Knowledge: Familiarity with AI/ML concepts. Hands-on experience with large language models (LLMs), and prompt engineering techniques are strongly preferred.
  • AI Agent Frameworks: Strong understanding of general AI agent frameworks, function calling, and retrieval-augmented generation (RAG). Hands-on experience of building such a system is strongly preferred.
  • Cloud & DevOps: Experience with cloud platforms (AWS, GCP, or Azure) and DevOps practices (CI/CD, containerization, monitoring).
  • Integration Expertise: Hands-on experience with integrating systems via APIs, webhooks, and data pipelines.
  • Communication: Excellent communication and project management skills.
  • Analytical Approach: Ability to use data-driven decision-making, including A/B testing and performance monitoring, to refine solutions.
  • Collaborative Builder: You thrive in cross-functional environments, working hand-in-hand with PMs and engineers to turn real customer problems into scalable AI solutions.

Note on Our Hiring Process

We highly value your time and engineering craftsmanship. To ensure a streamlined and objective process, the first step for qualified applicants following an initial resume review is a self-paced CoderPad technical assessment. This allows you to showcase your practical coding and problem-solving skills in a real-world environment before moving into conversational interview rounds.

Perks & Benefits:

We offer a comprehensive and people-first benefits package to support you at work and in life:

  • We offer Cresta employees a variety of medical benefits designed to fit your stage of life
  • Flexible vacation time to promote a healthy work-life blend
  • Paid parental leave to support you and your family

Compensation at Cresta

Cresta’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email).

Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed.

Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates’ personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.

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