Engineering Lead
On-siteBengaluru, Karnataka, India
Job Summary
Lead the design and development of Aion's core enterprise AI platform, ensuring scalability, reliability, and performance across distributed systems and cloud infrastructure. Drive high-level architecture discussions, establish engineering standards, and make strategic technical decisions balancing product requirements with long-term platform sustainability. Mentor a high-performing team of software engineers, foster a culture of ownership and continuous learning, and support hiring, onboarding, and career development. Partner closely with Product, Design, and Customer Success teams to translate business requirements into scalable technical solutions while driving project planning and execution. Build resilient, highly available systems capable of supporting enterprise-scale AI workloads and optimize CI/CD pipelines and operational readiness. Work with executive leadership to align engineering strategy with business objectives and represent engineering in customer discussions and strategic planning sessions.
Required Qualifications
- 8+ years of experience building and scaling software platforms, distributed systems, or enterprise applications
- 2+ years of experience leading engineering teams in a fast-paced startup or high-growth environment
- Deep understanding of distributed systems, microservices architecture, cloud-native applications, and API design
- Experience with Kubernetes, Docker, cloud platforms, and Infrastructure-as-Code
- Strong knowledge of databases, caching systems, messaging platforms, and event-driven architectures
- Experience building highly scalable, low-latency, production-grade systems
- Experience implementing observability using Prometheus, Grafana, OpenTelemetry, and distributed tracing
- Strong understanding of software security, authentication, authorization, and enterprise deployment practices
Desired Qualifications
- Strong proficiency in Golang is preferred
- Experience with Python, Rust, Java, or C++ is a plus
- Familiarity with AI infrastructure, LLM deployment, inference systems, orchestration platforms, or MLOps is highly desirable
- Experience building AI platforms, model serving infrastructure, orchestration systems, or enterprise AI products
- Experience with AWS, Azure, GCP, Kubernetes Operators, Terraform, or platform engineering
- Experience building multi-tenant SaaS platforms, customer VPC deployments, or on-premises enterprise solutions
- Experience building internal developer platforms, SDKs, APIs, developer tooling, or engineering productivity platforms
- Experience scaling engineering teams from early-stage startup to growth-stage organizations
- Founder-level ownership and bias for action
- Strong strategic thinking and ability to connect technical decisions to business impact
- Excellent communication and mentoring skills
- Thrives in ambiguity, fast-paced environments, and early-stage startup culture
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