ALOIS Solutions
Website:
aloissolutions.com
Job details:
Designation - Engineering Lead / Engineering Manager
Experience - 4 to 8 Years
Location - Onsite | Vadodara, Gujarat
An exciting opportunity with AKINO Labs, a growing core IT company within our business group.
A hands-on player–coach role owning engineering end to end - architecture and code, the infrastructure it runs on, the pipeline that ships it, the team that builds it and the plan that delivers it. Roughly half the week is technical; the other half is leading engineers, running delivery and keeping production healthy.
About AKINO Labs -
An AI-first technology product company headquartered in Vadodara. We design and build connected ecosystems of autonomous AI agents for enterprise, startup and government clients - automating work end to end across contract intelligence, invoice processing, HR operations,
customer service and conversation analytics. Real products in production, not demos.
Key Responsibilities -
Engineering & Architecture:
- Own system design and architecture across MERN, MEAN, MEVN and Python stacks - domain models, API contracts, service boundaries,
- integration patterns.
- Set non-functional requirements: performance budgets, scalability, availability, security posture and run-cost.
- Write production code on critical paths and run code reviews against explicit standards for testability, error handling and security.
- Own coding standards, branching strategy, automated test strategy and CI quality gates; manage technical debt as a tracked, funded item.
- Act as the escalation point for complex debugging, production incidents and performance bottlenecks.
DevOps, Infrastructure & Cloud Operations:
- Own the full SDLC toolchain - source control, CI/CD, artifact management and environment promotion from dev to production.
- Design and operate cloud infrastructure on AWS, Azure or GCP; containerise and orchestrate with Docker and Kubernetes or ECS.
- Move infrastructure to code (Terraform, CloudFormation, Bicep, Ansible) - no undocumented manual changes to production.
- Build observability into every service: centralised logging, metrics, tracing, alerting and an on-call rota.
- Run reliability and security practice - SLOs, backup and DR drills, secrets management, vulnerability scanning, least-privilege IAM, cloud cost control.
AI/ML & Modern Technology:
- Guide design of AI-enabled features: LLM integration, prompt and context design, RAG, embeddings, vector search and evaluation harnesses.
- Set standards for model selection, cost and latency budgets, guardrails, PII handling and human-in-the-loop review.
- Take AI proofs of concept to production-grade, multi-tenant, observable services with drift and regression monitoring.
- Bring AI-assisted engineering into the team's workflow with clear quality and IP controls.
Team Leadership:
- Lead, mentor and grow a cross-functional team of frontend, backend, full-stack, QA and DevOps engineers.
- Run 1:1s, goal setting, performance reviews and development plans; address under-performance early and fairly.
- Own capacity planning, skills mapping, technical interviews, the hiring bar and onboarding.
- Build engineering culture through design reviews, pairing, documentation and blameless post-mortems.
Delivery & Project Management:
- Own sprint planning, estimation, backlog refinement, release planning and delivery commitments with Product and Project teams.
- Break epics into shippable increments; manage dependencies, critical path and cross-team sequencing.
- Report engineering health on DORA and delivery metrics - deployment frequency, lead time, change failure rate, MTTR, defect leakage, predictability.
- Surface risks and slippage early with a recovery plan; represent engineering in client calls, demos and escalations.
- Support pre-sales with effort estimation, technical proposals and feasibility inputs.
Required Qualifications:
- 4–8 years in software engineering, including 1.5–2 years leading a team, squad or delivery pod.
- Deep hands-on strength in at least one JavaScript stack (MERN / MEAN / MEVN) plus working proficiency in Python.
- Production experience with cloud infrastructure, CI/CD and containers - designed, shipped and operated under real load.
- Working understanding of AI/ML and LLM application patterns, with judgement on where they fit and where they do not.
- Proven track record running Agile delivery and coordinating with Product and Project teams.
- Strong debugging instincts - comfortable in logs, traces, profilers and query plans.
- Clear written and verbal communication in English, including with international stakeholders.
- B.E. / B.Tech / MCA / M.Sc. in CS or IT, or equivalent practical experience.
Click on Apply to know more.
