Applied AI Engineer

Simbian Inc; Bengaluru; Hybrid; INR 3,500,000 - 6,000,000; Full time

Job summary

Simbian in Bengaluru (Remote) is building an Agentic AI platform for cybersecurity. We seek an Applied AI Engineer to shape agent behaviors, back-end systems, and real-world security workflows, collaborating with research, product, and security teams.

You will design multi-step agent workflows, tool integration, memory and retrieval layers, and production-grade backends for AI agents, delivering secure, scalable solutions across enterprise environments.

Qualifications

• 4–7 years of professional software engineering experience.
• Strong backend development experience, preferably with Python, Go, or Node.js.
• Strong understanding of distributed systems fundamentals.
• Experience with microservices, APIs, asynchronous execution, and event-driven systems.
• Hands-on experience with LLMs / Generative AI / Applied AI.
• Experience with at least some of: Agent frameworks.
• Experience building and deploying production software.
• Ownership mindset and ability to take a problem from zero to shipped.

Skills

Backend development

Distributed systems

APIs & microservices

LLMs / AI

Agent frameworks

Production software

Problem solving

Ownership

Education

Strong academic background in Computer Science

Tools

LangGraph

LangChain

AWS

GCP

Azure

Docker

Kubernetes

CI/CD

Job description

Bangalore (Remote), India, India | Posted on 08/10/2026

Simbian® is building Agentic AI platform for cybersecurity. Founded by repeat successful security founders, we have gathered an excellent cohort of employees, partners, and customers.

Our mission is to solve security using AI and our core values are excellence, replication, and intellectual honesty.

Our promise is to make Simbian the best workplace of your career and we believe a small group of thoughtful passionate people can make all the positive difference in the world.

To fuel our fast growth, we are seeking an exceptional candidate who shares our core values of excellence (being the world's best at our craft), replication (share your best ideas with others), and intellectual honesty (tell the truth even if it's bitter).

Our AI Agents automate security operations and provide our customers 10x leverage. Our customers include some of the world's largest companies. Our initial use cases include:

• SOC alert triage and investigation
• Prioritization and classification of vulnerabilities
• AI based threat hunting

Job Description

About SimbianSimbian is building an Agentic AI platform for cybersecurity. Our AI agents automatesecurity operations and provide customers with 10x leverage across critical securityworkflows.

Our initial use cases include:

• AI-based SOC alert triage and investigation
• AI-based Penetration Testing

Founded by repeat successful security founders, Simbian brings together a strong team ofengineers, security experts, and operators working on some of the hardest problems at theintersection of cybersecurity and AI.Our core values are excellence, replication, and intellectual honesty. We believe inbuilding exceptional technology, sharing what we learn, and being honest about whatworks—and what doesn't.

The Role

We are looking for an Applied AI Engineer to help build the systems that make our AIagents powerful, reliable, and useful in real-world cybersecurity environments.This role sits at the intersection of backend engineering, distributed systems, andapplied AI.You will build the backend infrastructure that powers our agents while also working directlyon agent behavior—improving how agents reason, use tools, retrieve context, handlefailures, and complete complex tasks.The goal isn't simply to build models or backend services in isolation. It's to turn AIcapabilities into dependable production systems that solve real customer problems.You'll work closely with research, engineering, product, and security teams to take ideasfrom experimentation to production and measure whether they improve agentperformance.

Requirements

Applied AI & Agent Systems

• Design and iterate on AI agent behaviors across real-world cybersecurity andsoftware engineering workflows.
• Build multi-step agent workflows with tool calling, branching logic, retries,validation, and human-in-the-loop controls.
• Develop tool schemas, execution strategies, context construction, memory, andretrieval mechanisms that improve agent performance.
• Experiment with prompting, model-facing strategies, tool-use patterns, and contextengineering.
• Analyze agent failures and systematically turn failure modes into product andengineering improvements.
• Build guardrails, policy layers, and safe-execution mechanisms for agents operatingin security-sensitive environments.
• Help define what "good" looks like for an agent completing complex tasks end-toend.

Evaluation & Agent Performance

• Design and run evaluations to measure agent quality, reliability, regressions, andedge cases.
• Build evaluation pipelines, test harnesses, scoring frameworks, and goldendatasets.
• Create feedback loops that bring real-world task data and production failures backinto evaluation and development.
• Analyze production traces and agent behavior to identify opportunities for improvingsolve rate, usefulness, and reliability.
• Work with research and engineering teams to translate experimental improvementsinto measurable production gains.
• Design and build scalable backend services that power AI agents and cybersecurityworkflows.
• Build high-scale, multi-tenant systems that securely support multiple customerenvironments.
• Work with microservices, asynchronous execution, event-driven architectures, anddistributed systems.
• Build ingestion, indexing, retrieval, and agent-memory layers for large volumes ofsecurity data.
• Design reliable execution systems with strong observability, traceability,monitoring, and data-quality guarantees.
• Build and maintain integrations with enterprise security platforms such as SIEM,SOAR, EDR, and NDR systems.
• Own features end-to-end—from architecture and implementation throughdeployment, monitoring, debugging, and iteration in production.

Product & Cross-functional Collaboration

• Work closely with product, research, infrastructure, and security teams to turnambiguous problems into working systems.
• Partner with customer-facing teams to understand real-world failures and improvethe product based on user needs.
• Help shape the interfaces and workflows through which users interact with AIagents.
• Contribute to architectural decisions and technical direction as the platformevolves
• Have 5–8 years of software engineering experience, with strong backenddevelopment experience.
• Have experience building and shipping ML/LLM-powered products or AI-enabledfeatures, or have strong hands-on experience applying LLMs to real engineeringproblems.
• Are highly proficient in Python and comfortable working with modern AI/ML tooling.
• Have strong fundamentals in distributed systems, backend architecture, APIs,microservices, and asynchronous systems.
• Have experience with LLMs, prompt engineering, RAG, embeddings, modelevaluation, or agentic systems.
• Think beyond model metrics and engineering elegance—you care about whetherthe system actually works for users.
• Enjoy debugging messy, real-world failures and turning them into systematicimprovements.
• Are comfortable working in ambiguous environments and taking ownership from problem definition → implementation → production.
• Have a strong understanding of software engineering fundamentals and write clean,maintainable, well-tested code.
• Enjoy reading technical papers, RFCs, experimenting with new technologies, andlearning quickly.

Must Have

• 4–7 years of professional software engineering experience.
• Strong backend development experience, preferably with Python, Go, or Node.js.
• Strong understanding of distributed systems fundamentals.
• Experience with microservices, APIs, asynchronous execution, and event-drivensystems.
• Hands-on experience with LLMs / Generative AI / Applied AI.
• Experience with at least some of:
  • Agent frameworks
• Experience building and deploying production software.
• Strong problem-solving and debugging skills.
• Ownership mindset and ability to take a problem from zero to shipped.

Bonus / Great to Have

• Experience building AI agents or tool-using LLM systems.
• Experience with LangGraph, LangChain, or similar agent frameworks.
• Experience with model evaluation, fine-tuning, or code-generation models.
• Experience building developer tooling or AI coding systems.
• Experience with cybersecurity products, particularly SIEM, SOAR, EDR, NDR, orsecurity data pipelines.
• Experience with AWS/GCP/Azure, Docker, Kubernetes, and CI/CD.
• Experience building evaluation frameworks, benchmark datasets, or automatedtesting systems for AI agents.
• Experience with agent observability, tracing, and production LLM monitoring.
• Strong academic background in Computer Science or a related field; graduatesfrom IITs or other top-tier engineering institutions preferred.
• Build an AI-first cybersecurity platform from the ground up.
• Work at the intersection of AI, cybersecurity, and distributed systems.
• Solve problems where there isn't always an obvious playbook.
• Work directly with founders, researchers, security experts, and engineering leaders.
• Own meaningful problems end-to-end and see your work go directly intoproduction.
• Be part of an early team where your technical decisions and ideas can haveoutsized impact.
• Ship fast, learn fast, and build systems that matter.