Experience: 6.00 + years
Salary: Confidential (based on experience)
Expected Notice Period: 15 Days
Shift: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type: Office ()
Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: Skit.ai)
(*Note: This is a requirement for one of Uplers client - Skit.ai)
What do you need for this opportunity?
Must have skills required:
ISO, Basetan, Deepgram, AWS, Azure, Google Cloud Platform
Skit.ai is Looking for:
About us:
Skit.ai is the pioneer Conversational AI company transforming collections with omnichannel GenAI-powered assistants. Skit.ai’s Collection Orchestration Platform, the world’s first solution, streamlines collection conversations by syncing channels and accounts. Skit.ai’s Large Collection Model (LCM), a collection LLM, powers the strategy engine to optimize interactions, enhance customer experiences, and boost bottom lines for enterprises. Skit.ai has received several awards and recognitions, including the BIG AI Excellence Award 2024, Stevie Gold Winner 2023 for Most Innovative Company by The International Business Awards, and Disruptive Technology of the Year 2022 by CCW. Skit.ai is headquartered in New York City, NY.
Job Title: Senior Multi-Cloud AI DevOps Engineer
Location: Bangalore (Full Time On Site)
Experience: 6+ years
Type: Full-time
Key Responsibilities:
Multi-Cloud Infrastructure Architecture
- Design production-grade infrastructure across AWS, GCP, and Azure Architect private, low-latency interconnects between clouds
AWS Direct Connect
GCP Cloud Interconnect
Azure ExpressRoute
- Dedicated cross-cloud networking solutions
- Deploy multi-region infrastructure for HA and DR
- Implement IaC (Terraform, Pulumi, CloudFormation) across all clouds
AI/ML Services & API Integration
- Deploy and optimize Google Gemini APIs, Vertex AI APIs, Bedrock APIs
- Implement ASR/STT services
Deepgram
Google Cloud Speech-to-Text
Azure Speech Services
Whisper
Baseten
More
Configure TTS services
Google Cloud TTS
Azure Speech
ElevenLabs
Implement model serving infrastructure for fine-tuned models
Security & Network Engineering
- Design Zero Trust network architectures across multi-cloud
- Configure VPCs, VNets, security groups, NACLs, firewall rules
- Implement private endpoints and PrivateLink configurations
- Set up VPN tunnels, peering connections, transit gateways
- Implement secrets management, encryption, key rotation
- Maintain compliance: SOC 2, ISO 27001, ISO/IEC 42001, if not practical, theoretical understanding of AI regulated compliances like ISO/IEC 42001:2023, ISO/IEC 27001is must
Compute & Container Orchestration
- Create and manage VMs, instance groups, auto-scaling
- Deploy Kubernetes clusters (EKS, GKE, AKS)
- Implement GPU compute infrastructure
NVIDIA A100, H100
TPUs
- Optimize compute costs while meeting performance SLAs
Performance & Reliability
- Design for sub-100ms latency in voice AI pipelines
- Implement monitoring and observability
Datadog
Grafana
CloudWatch
Cloud Monitoring
- Build automated incident response and self-healing infrastructure
- Conduct performance testing, load testing, capacity planning
Experience
Required Qualifications
- 6+ years hands-on cloud infrastructure experience
- 3+ years working across multiple cloud providers simultaneously
- Proven track record with production AI/ML workloads
- Deep expertise in at least 2 of: AWS, GCP, Azure
- Experience with real-time voice/audio systems
Technical Skills — Must Have
AWS EC2
GCP Compute Engine
Azure VMs
Creation, configuration, hardening, lifecycle management
VPCs, subnets, route tables, NAT gateways
Load balancers (ALB, NLB, Cloud Load Balancing, Azure LB)
DNS (Route 53, Cloud DNS, Azure DNS)
VPN tunnels
Direct Connect / Cloud Interconnect / ExpressRoute
PrivateLink / Private Service Connect
Transit gateways
Hub-spoke architectures
Multi-cloud mesh
Kubernetes (EKS, GKE, AKS)
Docker, Helm
Service mesh (Istio, Linkerd)
Terraform (required)
CloudFormation
Pulumi
ARM templates
IAM, RBAC
Security groups, NACLs
WAF, DDoS protection
Secrets management (Vault, Secrets Manager)
GitHub Actions, GitLab CI
Cloud Build, CodePipeline
Security scanning integration
- AI/ML Infrastructure — Must Have
Google Gemini APIs / Vertex AI or equivalent LLM platforms
Production STT deployment (Deepgram, Google Speech, Azure Speech, Whisper)
Production TTS deployment (Google TTS, Azure TTS, ElevenLabs)
Model serving patterns, GPU allocation, inference optimization
Real-time streaming protocols (WebRTC, WebSocket, gRPC)
Nice to Have
- LiveKit, Twilio, or similar real-time communication platforms
- Telephony/VoIP background (SIP trunking, PSTN integration)
- MLOps: model versioning, A/B testing, canary deployments
- FinOps: cost optimization, reserved/spot instances
- Certifications
AWS Solutions Architect Professional
GCP Professional Cloud Architect
Azure Solutions Architect Expert
AI governance frameworks (ISO/IEC 42001:2023)
What Were NOT Looking For
- Someone who can learn quickly — we need proven production experience
- Single-cloud specialists who only know others from documentation
- DevOps generalists without deep AI/ML infrastructure experience
- Candidates without hands-on cross-cloud connectivity experience
How to apply for this opportunity?
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
About Uplers:
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.
(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, dont hesitate to apply today. We are waiting for you!