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Software AI Engineer
Tredence
Bengaluru
2-8 years
Today
$20.5K–33.7K/yr
Full-time
Onsite
Skills Required
LLM
RAG
Agentic AI
OpenAI
Azure OpenAI
Claude
Gemini
vLLM
AI Platform
Multi-Agent Systems
Kubernetes
GKE
GCP
Cloud Run
BigQuery
Description
Tredence is hiring a hands-on AI Engineering Lead for its Enterprise AI Platform. The role focuses on building, operating, and scaling AI agent systems, RAG applications, and platform infrastructure.
Company: Tredence
Role: Software AI Engineer
Location: Bangalore, India
Experience
- 2 to 8 years
- 5 years
- Hands-on leadership in AI platform and systems engineering
- Strong production experience with Kubernetes, preferably GKE
- Strong hands-on experience with Google Cloud Platform
- Proven experience leading complex engineering initiatives or mentoring teams
Responsibilities
- Lead the architecture and development of AI platforms supporting agents, workflows, RAG systems, and LLM-based applications
- Define best practices for AI system design, model orchestration, inference pipelines, and runtime infrastructure
- Drive the evolution of AgentOps frameworks for managing AI agents at scale
- Provide technical leadership and mentorship to engineers working on AI infrastructure and platform systems
- Collaborate cross-functionally with AI Research, Product, and Platform teams to deliver production-grade AI solutions
- Establish engineering standards, design patterns, and development practices
- Design and manage AI agent architectures, workflow orchestration, and multi-agent systems
- Build and operate Model Gateways and LLM routing layers across providers
- Lead development of RAG systems with vector databases and retrieval pipelines
- Optimize latency, throughput, and cost of AI workloads
- Own Kubernetes-based platforms for scalable AI workloads
- Design and implement cloud-native architectures across GCP, with AWS and Azure as secondary environments
- Lead Infrastructure as Code and platform automation initiatives
- Establish CI/CD and GitOps-based deployment models for AI systems
- Define and implement SRE practices including monitoring, logging, tracing, and incident management
- Architect observability using OpenTelemetry, Prometheus, Grafana, ELK, or Cloud Monitoring
- Drive production readiness, scalability planning, and disaster recovery strategies
- Ensure AI platform compliance with enterprise-grade security and governance standards
- Implement IAM, RBAC, SSO, secrets management, and network security controls
- Support customer deployments across cloud, hybrid, and on-prem environments
- Own end-to-end system delivery and operational excellence
Nice To Have
- Experience with self-hosted LLM infrastructure
- Hands-on with vector databases
- Knowledge of Service Mesh
- Experience with workflow orchestration tools
- Exposure to Platform Engineering and Internal Developer Platforms
- Understanding of FinOps and cost optimization for AI workloads
Other:
- Powered by Ripplehire
- Careers at Tredence
- Job ID: 8995062
- 1 opening
- Full-time
- Enterprise AI Platform powering AI Agents, Multi-Agent Systems, RAG Applications, AI Workflows, and Knowledge Platforms
- AgentOps and AI Platform engineering efforts
- Enterprise-ready across cloud and hybrid environments
- GKE preferred
- GCP primary, AWS and Azure secondary
More Skills
AI platforms, RAG applications, knowledge platforms, LLM-based applications, model orchestration, inference pipelines, AgentOps, vector databases, retrieval pipelines, TGI, Ollama, Pub/Sub, IAM, VPC, Monitoring, containerization, autoscaling, networking, storage, high availability, distributed systems, event-driven architectures, Terraform, Infrastructure as Code, CI/CD, GitOps, ArgoCD, Flux, Prometheus, Grafana, OpenTelemetry, ELK, Cloud Monitoring, SRE, incident management, IAM, RBAC, SSO, secrets management, network security, cloud-native architectures, AWS, Azure, Pinecone, Qdrant, Weaviate, pgvector, Istio, Linkerd, Temporal, Airflow, Dagster, Platform Engineering, Internal Developer Platforms, FinOps
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