7 дней назад
Senior AI Software Development Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior AI Software Development Engineer (Gemini/Vertex AI): Building secure, scalable enterprise agent orchestration systems and reusable high-code components with an accent on LLM integrations, RAG, observability, and governance. Focus on designing multi-agent workflows, optimizing inference performance and cost, and implementing secure integrations with enterprise platforms and internal APIs.
Location: Hyderabad, India
Company
develops cybersecurity and application delivery solutions that help organizations create, secure, and run applications.
What you will do
- Build and optimize enterprise agent orchestration frameworks supporting tool use, memory, RAG, multi-agent workflows, and automation.
- Integrate Gemini models through Vertex AI and develop reusable SDKs, abstractions, and high-code agent libraries in Python and another supported language.
- Implement secure integrations with Salesforce, Snowflake, SharePoint, ServiceNow, and internal APIs, including MCP servers and API gateways.
- Build observability, evaluation, safety, and governance capabilities covering telemetry, guardrails, prompt injection defense, RBAC, and compliance.
- Support engineering teams adopting Gemini Code Assist and internal AI platforms through documentation, code samples, reviews, and technical guidance.
- Improve agent performance through latency optimization, parallelization, caching, streaming, batching, benchmarking, and cost management.
Requirements
- 6+ years of software engineering experience with distributed systems and backend architecture.
- Deep production coding expertise in Python and at least one of Go, Java, or TypeScript.
- Production experience with LLM systems, including prompt engineering, tool calling, RAG, embeddings, and agent frameworks.
- Experience with Vertex AI, Gemini APIs, OpenAI APIs, or similar enterprise AI platforms.
- Strong knowledge of API design, microservices, cloud-native architectures, Docker, and Kubernetes.
- Experience with orchestration frameworks, vector databases, retrieval strategies, authentication, authorization, and enterprise security patterns.
Nice to have
- Experience building multi-agent systems or autonomous workflow engines.
- Experience with model evaluation pipelines, AI quality metrics, structured output enforcement, or inference optimization.
- Experience with Snowflake, Salesforce, ServiceNow, SharePoint, internal developer platforms, or SDK ecosystems.
Culture & Benefits
- Work contributes to the rollout of agentic AI across engineering, sales, support, finance, and product teams.
- Emphasis on secure data handling, enterprise reliability, governance, and compliance.
- promotes an inclusive workplace and provides reasonable accommodations during the application process.
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