CyRAACS is building the next generation of intelligent, scalable systems at the intersection of robust backend engineering and cutting-edge AI. We are a fast-moving, high-trust team that ships consequential software and values deep technical ownership. Our engineers solve hard problems, influence product direction, and building the next generation of talent.
Role Overview
We are looking for a senior technical professional who is genuinely exceptional — someone who combines the depth of a specialist with the breadth of a systems thinker. You will be the hands on technical architect who owns our backend platform and AI/ML initiatives, driving architectural decisions, and design/development complex solutions end-to-end.
This is an individual contributor (IC) role with outsized organisational impact. You will be expected to operate fluidly across multiple leadership dimensions — guiding architecture through others, write code, design review, unblocking critical decisions, and mentoring the next generation of engineers — not just execute on assigned tasks. Your work will shape engineering culture, accelerate team velocity, and directly influence CyRAACS’s most critical products.
Key Responsibilities
Technical Leadership & Architecture
- Own and evolve the end-to-end architecture of core backend services — design for scale, reliability, and maintainability from first principles.
- Define and drive technical design/architecture in collaboration with product and engineering leadership.
- Lead design reviews, architecture decision records (ADRs), and cross-team technical forums.
- Identify systemic risks and bottlenecks; champion proactive remediation before they become incidents.\
- Design and build high-throughput, low-latency distributed systems and microservices using Java (Spring Boot) and/or Python.
- Enforce best practices in API design (REST / gRPC), data modelling, and service contracts.
- Drive performance engineering — profiling, benchmarking, and optimisation of critical code paths.
- Own reliability engineering: SLOs, error budgets, observability (metrics, traces, logs), and runbooks.
AI / ML Platform & Integration
- Architect and implement AI-powered features spanning model serving, inference pipelines, and real-time data flows.
- Collaborate with data scientists to productionise ML models — translate research artefacts into robust, observable services.
- Build and optimise MLOps tooling: feature stores, experiment tracking, model registries, and CI/CD for ML.
- Evaluate and integrate LLM / GenAI capabilities into product surfaces; reason clearly about trade-offs in latency, cost, and safety.
- Mentor and grow senior engineers; conduct rigorous code and design reviews that raise the entire team’s bar.
- Act as a technical multiplier — proactively remove blockers, share knowledge, and build engineering leverage across the team.
Must-Have Qualifications
Education
- B.Tech / B.E. / M.Tech in Computer Science, Information Technology, or a related discipline from an NIT, IIT, BITS Pilani, or equivalent Tier-1 institution.
Experience
- 8 – 14 years of progressive software engineering experience, with at least 3 years operating at a staff / principal / architect level.
- Demonstrable track record of designing and shipping large-scale distributed systems in production.
- Hands-on experience working on both backend platform engineering and AI / ML workloads — not just one or the other.
Core Technical Skills
- Java (primary): Expert-level proficiency — deep knowledge of the JVM, concurrency, memory model, performance tuning, and modern Java (17+).
- Python (strong working knowledge): Used extensively for data pipelines, ML integrations, and scripting.
- Distributed systems: Strong grasp of CAP theorem, consensus algorithms, event-driven architectures, Kafka / Pulsar, and database internals.
- Cloud-native: Solid experience with AWS / GCP / Azure; container orchestration (Kubernetes / ECS); infrastructure-as-code (Terraform / Pulumi).
- AI / ML engineering: Experience productionising ML models; familiarity with frameworks such as PyTorch, TensorFlow, or JAX; working knowledge of LLMs and vector databases.
- Data platforms: Comfortable with OLTP (PostgreSQL, MySQL) and OLAP (Snowflake, BigQuery, ClickHouse) systems; streaming (Spark Streaming, Flink).
Good-to-Have Skills
- Experience with real-time inference serving (Triton, vLLM, BentoML, or equivalent).
- Contributions to open-source projects or published technical writing / conference talks.
- Prior startup experience or experience scaling a product from zero to significant user base.
- Familiarity with security engineering, zero-trust architectures, or compliance frameworks (SOC 2, ISO 27001).
- Knowledge of Rust, Go, or Scala for polyglot environments.
Why Join CyRAACS?
- Greenfield opportunity to architect systems that matter — your fingerprints will be on every major technical decision.
- Collaborative, high-trust engineering culture that values craft, curiosity, and candour.
- Work at the bleeding edge of backend scalability and applied AI.
- Amazing leadership team; outcome-oriented culture.