or apply directly on TribalScale's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 78 days TribalScale's roles stay open a median of 59 days
- Reposted
- No
- Salary listed
- No 0% of TribalScale's roles list one
- Ghost-job risk at TribalScale
- high 9 stale, 0 reposted of 14 open
- Hiring momentum
- 18 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-23
Measured from postings appearing on and disappearing from TribalScale's own greenhouse board since 2026-08-03. Full hiring picture for TribalScale.
About this role
As a Forward Deployed Engineer at TribalScale, you will engage directly with clients to understand their business challenges and translate them into technical solutions. Your role involves designing and deploying AI-enabled applications, engineering systems around AI models, and collaborating with cross-functional teams to deliver production-quality software. You will also be responsible for troubleshooting, establishing engineering practices, and ensuring the reliability and performance of AI applications.
- benefits
- 1/5
- freshness
- 1/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of TribalScale as an employer.
What you need
- Professional experience building and deploying production-grade software, ideally including AI-powered or agentic systems.
- Strong proficiency in Python, TypeScript, or another language commonly used to build AI applications, platforms, and developer tooling.
- A practical understanding of harness engineering: designing the infrastructure, context, tools, permissions, controls, and feedback mechanisms that enable AI agents to operate reliably.
- Experience building or working with agent loops, including planning, tool selection, execution, observation, reflection, recovery, and termination.
- Familiarity with graph-based orchestration, state machines, and multi-step workflows for coordinating agents, tools, data, and human approvals.
- Experience designing evaluation systems for AI applications, including task-based benchmarks, regression suites, model-graded evaluations, human review, and production monitoring.
Nice to have
- Experience with agent frameworks, workflow engines, coding agents, or custom model-orchestration systems.
- Experience creating tool interfaces, execution sandboxes, permission models, and human-in-the-loop controls for autonomous or semi-autonomous systems.
- Familiarity with retrieval-augmented generation, embeddings, vector search, knowledge graphs, fine-tuning, and model-routing strategies.
- Experience evaluating AI systems using golden datasets, simulators, adversarial testing, online experiments, and production feedback.
- Familiarity with AI observability, including traces, token and cost analysis, latency measurement, failure classification, and quality dashboards.
Worth weighing
- No salary listed.
- Role requires direct customer interaction and adaptability to changing requirements.
- Focus on AI and agentic systems may not appeal to all software engineers.
- Expectations for travel to client sites may be a consideration for some candidates.
Summarised from TribalScale's posting. Read the full original.
Listed by TribalScale on their greenhouse job board, last confirmed open on 2026-10-23. PitchMeAI is not the employer.
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