Senior Forward Deployed Applied Scientist I (Agentic AI)

Digital Ocean
Bengaluru
Workplace: HybridFull timeFunction: Research & Scientific (R&D)Experience: 4+ yearsEducation: mastersSkills: ["Ownership","Customer empathy","Technical communication","Collaboration","Bias for action"]

Embed with startups and AI-native enterprises to design, build, and deploy production-ready agentic workflows powered by DigitalOcean’s AI infrastructure. Architect multi-agent frameworks and autonomous reasoning loops, prototype new approaches with LangGraph/AutoGen, and harden systems with reusable evals and safety guardrails. Serve as a key feedback bridge between customer field deployments and core AI/ML product teams, with up to 30% travel for customer engagements.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Digital Ocean
Digital Ocean
4 days ago

Senior Forward Deployed Applied Scientist I (Agentic AI)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 21 hours agoStatus: Live

Job Summary

Embed with startups and AI-native enterprises to design, build, and deploy production-ready agentic workflows powered by DigitalOcean’s AI infrastructure. Architect multi-agent frameworks and autonomous reasoning loops, prototype new approaches with LangGraph/AutoGen, and harden systems with reusable evals and safety guardrails. Serve as a key feedback bridge between customer field deployments and core AI/ML product teams, with up to 30% travel for customer engagements.
Location: Bengaluru
Workplace: Hybrid
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Architect and implement production-ready agentic frameworks, including multi-agent workflows and autonomous reasoning loops.
  • •Embed directly with customers to transform ambiguous requirements into deterministic AI/agentic workflows.
  • •Prototype agentic frameworks (e.g., LangGraph, AutoGen) and harden them for enterprise production with stateful memory.
  • •Develop reusable eval frameworks and safety guardrails to monitor precision, execution security, latency, and cost efficiency.
  • •Convert field deployment friction into platform enhancements by partnering with core AI/ML product teams.
Travel: Medium travel

Pay and Benefits

Equity and Bonus:Equity
Perks:EquityPaid LeaveLearning Budget

Key Requirements

  • •4+ years hands-on experience in Applied AI, Machine Learning, or Data Science.
  • •Proven expertise building multi-agent orchestration engines, tool-use/function-calling pipelines, MCP, structured outputs, dynamic planning, and persistent memory models.
  • •Strong skills in production-ready Python and systems engineering, including Pydantic, FastAPI, Asyncio, and PyTorch.
  • •Ability to communicate complex AI trade-offs and collaborate directly with client teams (CTOs, AI leads).
  • •Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related technical field.
Experience:4+ yearsApplied aiMachine learningData science
Education:Master's in Computer Science, Machine Learning, AI (or related technical field)
Skills:OwnershipCustomer empathyTechnical communicationCollaborationBias for action
Languages:English
Tech Stack:PythonPydanticFastAPIAsyncioPyTorchTensorFlowLangGraphAutoGenLLMsVLMTransformersState space modelsMCPStructured outputs

Company Brief

Digital Ocean
Provides cloud infrastructure and developer-focused cloud services including scalable droplets, managed databases, Kubernetes, object storage, and networking to simplify deploying and managing applications for developers and small-to-medium businesses.
Industry: Cloud Computing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 250M to 500M
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York, United States
Founded: 2011
Glassdoor
Glassdoor: 3.8
WebsiteLinkedIn