Senior Technical Recruiter - Software Engineering & AI Talent Pipelines

At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges. Our work is about more than just AI—it’s about building the future through collaboration and innovation. We believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.

Join the Mission at TeamStation AI!

Where do we come from? We are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.

We are hiring a seasoned IT Recruiter with deep experience across software engineering.

This is not an HR generalist role. Not a coordinator role. And not somebody running keyword searches and pushing resumes.

60-MINUTE TECHNICAL INTERVIEW

Every candidate will complete a 60-minute technical interview: 11 evidence-based questions, five minutes each, with five minutes for transitions and close. The focus is technical recruiting, SDLC knowledge, evaluation integrity, and operating judgment.

This is not a coding test. It measures whether you understand the work well enough to recruit, screen, and move software talent through a serious technical pipeline.

The interview will cover:

• Recent software recruiting ownership, current AI use, and direct alignment to this role.
• The hardest technical search you personally closed, including market map, sourcing channels, funnel data, obstacles, and outcome.
• Turning a vague engineering request into a sourcing-ready and evaluation-ready Role Blueprint.
• Explaining the complete SDLC from product discovery through production incidents.
• Distinguishing senior backend, platform, DevOps, and SRE work by outcomes and ownership—not tool names.
• Designing a structured recruiter screen with explicit evidence for advance, reject, or no evidence.
• Challenging subjective LATAM rejection language such as “not polished enough” through transcript evidence and L2-aware evaluation.
• Diagnosing funnel conversion failures before burning more candidate pipeline.
• Building agentic recruiting workflows with human approval, failure handling, and measurable business impact.
• Leading junior sourcers while personally owning difficult searches.
• Measuring recruiting quality, quality of hire, ramp, retention, and post-start outcomes—not activity alone.

THE BASELINE

If you cannot show recent ownership of senior software-engineering searches, explain the SDLC and adjacent engineering roles, or describe a real AI workflow with human controls, this is not your role.

THE ROLE

You need to understand how modern software teams actually work across backend, frontend, platform engineering, cloud, DevOps and SRE, data engineering, AI and ML, security, QA automation, architecture, CI/CD, and the full SDLC.

Technical evaluator leads final technical evaluation with Platform Engineering. You must know enough to challenge a vague requisition, recognize weak evidence, build the right talent market, and prepare candidates for interviews tied to the real engineering work.

WHERE YOU SIT IN OUR ORG

• Lead 2 junior Recruiter/Sourcers.
• Work with 2 Senior Engineering Delivery Managers who run structured technical interviews.
• Partner with Platform Engineering on evaluation quality, workflow design, and system calibration.
• Partner with our Head of AI Talent Graph on global talent mapping, connected skill signals, warm pools, and market coverage.
• Work directly with our CEO and COO on priority roles, client risk, bottlenecks, and delivery commitments.
• Serve as a main client interface inside Slack and TeamStation. Clear answers. Clean evidence. No vague status reports.

WHAT YOU OWN

• Turn client demand into a clear Role Blueprint before sourcing starts. Define the business outcome, engineering work, stack, seniority, domain, team topology, interaction model, time zone, rate, risks, must haves, disqualifiers, interview plan, and decision owners.
• Lead the sourcing team. Set market strategy, assign searches, QA outreach, coach technical understanding, and stop low quality submissions before they reach clients.
• Use Nebula Talent Graph and Sirius search to find talent through skills, experience, relationships, adjacent capabilities, and market signals. Not keyword matching alone.
• Build evidence packs, not resume piles. Show why each candidate fits the work, where the risk is, what has been validated, and what still needs proof.
• Coordinate structured, scenario-based technical evaluation with our Engineering Delivery Managers. Generic code challenges are used only when they add real signal.
• Keep every stage, owner, decision, risk, SLA, and next action current in TeamStation. No shadow spreadsheets. No lost feedback. No candidate sitting for weeks.
• Track pipeline quality through stage conversion, stage aging, source quality, candidate drop-off, interview feedback speed, rejection quality, offer acceptance, and client decision time. After hire, connect the original evidence to 30-, 90-, and 180-day retention, ramp, hiring-manager satisfaction, and delivery outcomes.

THE AGENTIC WORK STANDARD

Using ChatGPT to write emails is not enough.

You build and operate agentic workflows for:

• Talent research and market mapping.
• Profile enrichment and semantic matching.
• Outreach preparation and follow-up.
• Candidate evidence packs and interview summaries.
• Pipeline QA, SLA alerts, and client updates.

Agents multiply the workload. Humans verify the evidence and own every hiring decision.

THE TALENT PIPELINE

You own this complete flow inside TeamStation:

1. Client intake and Role Blueprint.
2. Talent mapping, semantic search, and warm pools.
3. Recruiter screen and candidate evidence.
4. Structured technical interviews with our Engineering Delivery Managers.
5. Client decision, offer, and close.
6. Onboarding handoff and delivery outcome feedback.

FAIR TECHNICAL EVALUATION

We evaluate engineering signal, reasoning, and conceptual depth.

LATAM engineers may pause while thinking or translating. Accent, pauses, different wording, or a less polished interview style are not proof of weak ability or AI cheating. Integrity concerns require observable evidence and a second human review.

WHAT GOOD LOOKS LIKE

• The sourcers know exactly who to find and why.
• Engineering evaluators receive prepared candidates and clean context.
• Clients get evidence they can use to make a decision.
• Candidates move through no more than 3 stages unless another stage has a clear information-gain reason.
• Every rejection has a structured reason.
• Every candidate has a next action.
• TeamStation stays the source of truth.

This is a senior recruiting role for somebody who can operate technical talent as a system.