Senior Backend Engineer (AI)

Akila is hiring a Senior Backend Engineer who owns building and operating robust, scalable backend systems and services that power our AI and data products. While this is primarily a backend/infra role, we strongly prefer candidates with hands-on experience or strong interest in AI, Data Engineering, and MLOps. You’ll work across teams to design production APIs, data pipelines, model-serving infrastructure and monitoring — from scoping and implementation through deployment, observability, and iterative improvement. This role suits someone who can “vibe-code”: move fast, prototype sensibly, and cleanly productionize solutions while collaborating closely with product and ML teams.

Key duties and responsibilities

• Design, implement, and maintain backend services, APIs and microservices that power AI and product features.
• Build and operate data pipelines and ingestion systems (batch and streaming) for training and production workloads.
• Productionize AI features and model-serving pipelines (inference endpoints, RAG/vector search integrations, batching, caching).
• Optimize systems for latency, throughput, cost and reliability; troubleshoot production incidents and implement long-term fixes.
• Collaborate closely with AI engineers to translate model requirements or experimented codes into operational services and efficient infra patterns.
• Implement observability, logging, alerting, and SLOs for services and model performance (data drift, accuracy, latency).
• Ensure data quality, schema design, and secure data handling across services.
• Produce clear technical designs and documentation; communicate trade-offs to engineers and non-technical stakeholders.
• Mentor peers, contribute to team standards, and drive pragmatic engineering best practices.

Key Skills and Competencies

• Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or equivalent practical experience.
• 5+ years in backend or platform engineering (or combined backend + ML infra), with demonstrable experience shipping production services.
• Strong proficiency in Python and Java.
• Deep understanding of APIs, microservices, concurrency, caching, and performance optimization.
• Experience with containerization & orchestration: Docker, Kubernetes (deployments, autoscaling, networking).
• Solid experience with SQL and at least one NoSQL (MySQL, ClickHouse, TDEngine, Redis).
• Familiarity with message queues / task systems (Kafka, Redis Streams, Celery).
• Experience building or operating data pipelines / ETL (Airflow, Prefect, Spark, or similar).
• Practical knowledge of MLOps concepts and tooling (model packaging, model serving, CI/CD for models, monitoring model metrics).
• Strong debugging, system design and problem-solving skills; production troubleshooting experience.
• Good English communication and the ability to explain technical ideas to non-experts.
• Collaborative mindset and ability to work in a fast-moving startup environment (prototype → production).

Preferred / nice-to-have

• Hands-on experience building conversational AI or LLM-powered features (RAG, prompt engineering, embedding pipelines).
• GPU / inference stack familiarity: CUDA, cuDNN, TensorRT, NVIDIA Triton (for teams running heavy inference workloads).
• Experience with video analytics or real-time media pipelines (object detection/tracking, WebRTC, RTSP/HLS, low-latency batching).
• Experience with observability and SRE tooling: Prometheus/Grafana, ELK, Sentry, Open Telemetry.
• Background in cost-optimization for cloud infra and multi-tenant serving.
• Familiarity with privacy, security, and compliance considerations for ML/data products.