Senior DevOps Engineer

About This Role

Company Description

Hams.AI is an AI company building a full enterprise automation platform, enabling organizations to automate customer interactions, operational tasks, data-driven decisions, and service processes across voice, chat, WhatsApp, and digital channels.

Our platform focuses on real-time execution, turning enterprise workflows into automated actions across systems with measurable reliability, speed, and control at scale.

Hams is expanding rapidly across multiple industries in the region, and we are looking for deep backend engineering talent to strengthen our platform core.

About the Role:

Senior DevOps Engineer (8+ Years Experience)

Job Overview

We run a production Voice AI platform handling thousands of concurrent calls. This role owns the infrastructure that makes that possible — from SIP/RTP layer reliability and Asterisk/FreeSWITCH cluster management to LLM inference latency, real-time audio pipelines, and deployment automation.

You will work across infrastructure, security, and platform engineering to ensure our voice systems are fast, secure, and resilient. This is not a generalist DevOps role — we need someone who has been in the trenches of VoIP infrastructure and understands the unique demands of real-time voice AI at scale.

Key Responsibilities

VoIP & Telephony Infrastructure

• Design, deploy, and operate Asterisk and FreeSWITCH clusters at production scale.
• Manage SIP trunking, RTP media routing, DTMF handling, and dial plan configuration.
• Optimize codec performance (G.711, G.729, Opus) for latency, quality, and bandwidth efficiency.
• Implement SIP security controls: TLS/SRTP encryption, toll fraud prevention, SIP invite spoofing mitigation.
• Troubleshoot voice quality degradation, jitter, packet loss, and one-way audio issues across distributed infrastructure.
• Architect and maintain WebSocket/WebRTC infrastructure for real-time voice AI session handling.
• Manage concurrent session capacity and autoscaling for high call volume spikes.

Cloud, Containers & Scaling

• Design and operate Kubernetes clusters running high-concurrency, low-latency voice AI workloads.
• Build autoscaling strategies (HPA/VPA, cluster autoscalers) tuned for real-time audio processing demands.
• Optimize cloud infrastructure (AWS, GCP, or Azure) for voice AI latency, throughput, and cost efficiency.
• Architect multi-region, highly available environments with sub-second failover for live call infrastructure.
• Implement advanced networking configurations: QoS policies, UDP optimization, low-latency routing for RTP streams.

CI/CD & Deployment

• Build and maintain CI/CD pipelines with zero-downtime deployment strategies for voice services.
• Implement GitOps-based workflows, progressive delivery (blue-green, canary), and automated rollback mechanisms.
• Enforce artifact integrity, pipeline security scanning, and policy controls.
• Optimize pipelines for high deployment frequency without impacting live call sessions.

Security & Compliance

• Own security for call recording infrastructure, ensuring compliance with HIPAA, PCI-DSS, and regional data privacy regulations.
• Implement end-to-end encryption for audio streams and AI API traffic.
• Manage secrets, identity, and access controls across VoIP, AI platform, and cloud infrastructure.
• Conduct security reviews of SIP configurations, media servers, and telephony integrations.
• Integrate security scanning into CI/CD pipelines and establish vulnerability management processes.

Monitoring & Reliability

• Implement observability across the full voice AI stack: SIP signaling, media quality, AI inference latency, and call outcomes.
• Define and manage SLIs, SLOs, and error budgets for voice services and AI pipeline components.
• Own production incidents end-to-end — triage, remediation, postmortem, and follow-through.
• Design high-signal alerting that distinguishes media quality issues from infrastructure failures.
• Implement distributed tracing for real-time call flows across microservices.

Leadership & Collaboration

• Serve as technical escalation point for complex VoIP and voice AI infrastructure incidents.
• Mentor engineers in SRE, reliability, and telephony best practices.
• Lead architecture reviews and contribute to long-term infrastructure strategy and roadmap.
• Collaborate closely with AI/ML teams on inference infrastructure, model serving latency, and audio processing pipelines.

Required Qualifications

• 8+ years in DevOps, Site Reliability Engineering, or Infrastructure Engineering.
• Hands-on production experience with Asterisk and/or FreeSWITCH — dial plans, SIP configuration, media handling.
• Strong understanding of VoIP protocols: SIP, RTP/RTCP, SRTP, WebRTC.
• Experience scaling real-time voice or audio infrastructure under high concurrency.
• Proven security background: call recording compliance (HIPAA/PCI-DSS), SIP security hardening, secrets management.
• Strong experience with Infrastructure as Code (Terraform or CloudFormation).
• Deep Kubernetes knowledge: cluster operations, autoscaling, networking, production incident management.
• Experience with cloud platforms (AWS, GCP, or Azure) — especially networking and real-time workload optimization.
• Proficiency in Python, Bash, or Go for automation and tooling.
• Experience with monitoring and observability stacks (Prometheus, Grafana, ELK, distributed tracing).
• Strong Linux system administration and network troubleshooting skills.

Nice to Have

• Experience with AI speech services (OpenAI Whisper, Google Speech-to-Text, AWS Transcribe) or LLM inference infrastructure.
• Familiarity with Twilio, Telnyx, Vonage, or other CPaaS platforms.
• Experience with low-latency GPU or ML inference serving (TorchServe, Triton, vLLM).
• Background in conversational AI platform architecture.
• Familiarity with call center or contact center infrastructure.

Apply here: https://form.asana.com/?k=R4LckpjX9Q-8b2KrPMcNZg&d=1210838775195077