AI Agent Architect

Emergent
Bengaluru
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsSkills: ["Python","SQL","Experimentation","Product judgment","Systems thinking"]

Lead end-to-end development of AI agents that plan, build, test, and ship real software at global scale. Own experimentation, measurement, and rollout of agent capabilities, balancing product goals with reliability. Collaborate across product, engineering, and applied research to define success metrics and live-ready improvements.

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FursaFursa
Emergent
Emergent
2 months ago

AI Agent Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Lead end-to-end development of AI agents that plan, build, test, and ship real software at global scale. Own experimentation, measurement, and rollout of agent capabilities, balancing product goals with reliability. Collaborate across product, engineering, and applied research to define success metrics and live-ready improvements.
Location: Bengaluru
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Sr. Manager level

Key Responsibilities

  • •Develop deep, evidence-grounded intuition for how the agent thinks, succeeds, and fails across the full range of real-world use
  • •Mine production behavior for the failure modes, regressions, and bottlenecks most teams never see, and turn them into clear, quantitative signal
  • •Define and run high-leverage experiments that improve agent quality, reliability, and code outcomes, spanning prompt tuning, eval dataset creation, experimentation, and harness engineering
  • •Build and evolve evaluation frameworks that measure agent quality at scale: define the metric, build the dataset, validate it against known signals, and ship dashboards that make regressions impossible to miss
  • •Ship with rigor through clear metrics, evaluation gates, staged rollouts, and explicit rollback criteria
  • •Drive the hard problems in context engineering, memory systems, tool use, and long-horizon execution, where agent reliability is actually won or lost
  • •Make hard calls in subjective, probabilistic systems: when a regression is real, when a win is noise, when a benchmark is overfit, when to ship on mixed signals, and when to kill a promising direction
  • •Think like the agent and continuously make it smarter, more reliable, and more useful

Pay and Benefits

Perks:Meal AllowanceFamily InsurancePaid LeaveFlexible Hours

Key Requirements

  • •5+ years building and shipping software, with real end-to-end ownership
  • •At least 1 year of hands-on experience with agentic systems and their evaluation
  • •Strong systems thinking paired with sharp product judgment
  • •Hands-on with experimentation, metrics, and debugging, fluent in Python, SQL, or similar for analysis
  • •Comfortable reasoning about noise, confounds, distribution shift, and selection effects
Experience:5+ yearsAILLMsAgents
Skills:PythonSQLExperimentationProduct judgmentSystems thinking
Languages:English
Tech Stack:PythonSQLLLMs

Company Brief

Emergent
Provides a platform for orchestrating autonomous AI agents and workflows, enabling teams to build, deploy, monitor, and scale agent-driven applications and automations across business processes.
Industry: AI & Machine Learning
Growth: Early Stage Startup
Website