Sr. Technical Architect

Job Title: SRE Lead Engineer

Location: Hyderabad, India

Company: Client of Options Executive Search, AI Saas Product Development Company

We are seeking a DevOps / SRE Lead Engineer to architect and scale our client's multi-tenant SaaS platform with AI/ML at the core..

Our client, a fast-growing AI-powered SaaS company in the FinTech space, is looking for a Site Reliability Engineering (SRE) Lead Engineer to join their dynamic team. This is an opportunity to design and operate large-scale SaaS systems that integrate cutting-edge AI/ML capabilities.

About the Role

As the SRE Lead Engineer, you will be responsible for architecting, building, and maintaining infrastructure that powers a multi-tenant SaaS platform. You’ll drive reliability, scalability, and security, while supporting AI/ML pipelines in production. This is a hands-on role with significant ownership, requiring both technical depth and leadership in site reliability practices.

Key Responsibilities

• Architect, design, and deploy end-to-end infrastructure for large-scale, microservices-based SaaS platforms.
• Ensure system reliability, scalability, and security for AI/ML model integrations and data pipelines.
• Automate environment provisioning and management using Terraform in AWS (EKS-focused).
• Implement full-stack observability across applications, networks, and operating systems.
• Lead incident management and participate in 24/7 on-call rotation.
• Optimize SaaS reliability while enabling REST APIs, SSO integrations (Okta/Auth0), and cloud data services (RDS/MySQL, Elasticsearch).
• Define and maintain backup and disaster recovery for critical workloads.

Required Skills & Experience

• 8+ years in SRE/DevOps roles, managing enterprise SaaS applications in production.
• Minimum 1 year experience with AI/ML infrastructure or model-serving environments.
• Strong expertise in AWS cloud, particularly EKS, container orchestration, and Kubernetes.
• Hands-on experience with Infrastructure as Code (Terraform), Docker, and scripting (Python, Bash).
• Solid Linux OS and networking fundamentals.
• Experience in monitoring and observability with ELK, CloudWatch, or similar tools.
• Strong track record with microservices, REST APIs, SSO, and cloud databases.

Nice-to-Have Skills

• Experience with MLOps and AI/ML pipeline observability.
• Cost optimization and security hardening in multi-tenant SaaS.
• Prior exposure to FinTech or enterprise finance solutions.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related discipline.
• AWS Certified Solutions Architect (strongly preferred).
• Experience in early-stage or high-growth startups is an advantage.

Why Join?

• Be at the forefront of AI/ML-powered SaaS innovation in FinTech.
• Work with a high-energy, entrepreneurial team building next-gen infrastructure.
• Take ownership of mission-critical reliability challenges.
• Grow your career in an environment that values impact, adaptability, and innovation.

If you’re passionate about building secure, scalable, and intelligent platforms, we’d love to hear from you. Apply now to be part of our client’s journey in redefining enterprise finance operations.

Data Delivery Manager is responsible for managing and overseeing the end-to-end delivery of data

solutions, from data architecture and ingestion to processing, analysis, and reporting. This role

ensures that data projects are completed on time, within scope, and aligned with business

objectives. The Data Delivery Manager works with cross-functional teams, including data

engineers, analysts, and other stakeholders, to deliver high-quality data solutions. Key

Responsibilities: Project and Program Management: o Lead and manage the delivery of data-

driven projects, ensuring they are completed on time and within budget. o Develop and maintain

project plans, timelines, and resource allocation. o Monitor project progress and proactively

identify risks, implementing solutions to ensure successful project completion. o Ensure alignment

between data initiatives and business goals, maintaining continuous communication with

stakeholders. Stakeholder Engagement: o Serve as the primary point of contact between business

stakeholders and the data team, translating business requirements into technical specifications. o

Collaborate with business leaders to understand data needs and develop solutions that meet

those needs. o Provide regular updates on project status, risks, and key deliverables to

stakeholders and leadership teams. o Facilitate meetings to gather requirements and

communicate project milestones. Data Strategy & Architecture: o Oversee the design and

implementation of data solutions that support business objectives. o Ensure adherence to data

governance and quality standards throughout the data pipeline lifecycle. o Collaborate with data

architects to define scalable, secure, and high-performance data architectures. o Support data

integration initiatives across different platforms, ensuring smooth and efficient data flow. Team

Leadership and Development: o Manage cross-functional teams of data engineers, analysts, and

other professionals to deliver projects effectively. o Provide leadership and mentoring to team

members, fostering a culture of collaboration, innovation, and continuous learning. o Set clear

expectations, performance goals, and career development opportunities for the team. o Address

and resolve any team challenges, ensuring high levels of productivity and motivation. Quality

Assurance: o Ensure the accuracy, reliability, and quality of data solutions by implementing robust

testing, validation, and review processes. o Develop and enforce data standards, best practices,

and methodologies to ensure consistent, high-quality deliverables. o Drive continuous

improvement initiatives, analyzing past projects and identifying areas for enhancement. Risk

Management and Troubleshooting: o Identify potential risks to project delivery, including data

pipeline issues, resource shortages, or technical blockers, and implement mitigation strategies. o

Troubleshoot and resolve data-related issues and challenges during the project lifecycle.

Reporting and Analytics: o Oversee the creation and maintenance of data dashboards, reports, and

performance metrics. o Ensure that data solutions provide actionable insights for the business,

driving informed decision-making. Experience: o 5+ years of experience in managing programs

related to data management, data engineering, or analytics. o Proven track record in managing

data projects and delivering data solutions in a timely manner. o Experience with data integration,

data warehousing, and data modeling. o Strong understanding of data pipeline management, ETL

processes, and data analytics. Skills: o In-depth knowledge of data management tools and

technologies (e.g., SQL, NoSQL, ETL tools, cloud platforms such as AWS, Google Cloud, or Azure).

o Proficient in project management methodologies (Agile, Scrum, Waterfall). o Strong leadership

and team management skills, with the ability to drive collaboration across different functions. o

Excellent communication skills with the ability to translate complex data-related concepts into

understandable terms for non-technical stakeholders. o Analytical mindset with strong problem-

solving abilities. o Knowledge of data visualization and reporting tools (e.g., Power BI, Tableau,

Looker) is a plus. Certifications: o Project Management Professional (PMP) or Scrum Master

certification (preferred). o Data-related certifications (e.g., AWS Certified Big Data, Google

Professional Data Engineer) are a plus. Preferred Skills: o Experience with big data technologies

(e.g., Hadoop, Spark, Kafka). o Familiarity with machine learning or AI applications related to data

solutions. o Experience with data governance and compliance (e.g., GDPR).

Roles and Responsibilities

• Apply knowledge set to fetch data from multiple online sources, cleanse it and build APIs on top of it
• Develop a deep understanding of our vast data sources on the web and know exactly how, when, and which data to scrap, parse and store
• We're looking for people who will naturally take ownership of data products and who can bring a project all the way from a fast prototype to production.
• Integrating and maintaining Python services
• Developing robust microservices and applications

Desired Candidate Profile

• Strong relevant experience of at least 2-3 years.
• Strong coding experience in Python3.
• Should have good experience with Django and NodeJs.
• Proficient on modelling applications on both RDBMS and NOSQL databases
• Should have experience in web scraping
• Good understanding and hands-on with scheduling and managing tasks with cron
• Should have experience with microservice architecture
• Compile and analyze data, processes, and codes to troubleshoot problems and identify areas for improvement
• Should have experience in shell scripting, GIT and docker
• Writing unit tests for 100% code coverage.

• Contact potential or existing customers to inform them about a product or service
• Answer questions about products or the company
• Ask questions to understand customer requirements and close sales
• Direct prospects to the field sales team when needed
• Enter and update customer information in the database
• Take and process orders in an accurate manner
• Handle grievances to preserve the company’s reputation
• Go the “extra mile” to meet sales quota and facilitate future sales
• Keep records of calls and sales and note useful information