About the Role 

The Principal Sustaining and Forward Deployed Engineer is a senior individual contributor who ensures that Abacus Insights’ customers experience a stable, reliable, and high‑performing platform from day one through long‑term operation.

In this role, you serve as a technical partner to our customers—owning production operations, leading incident response, and safeguarding post‑launch reliability across the Abacus Insights ecosystem.

Your work blends:

• SRE‑driven production operations focused on customer uptime and trust

• SWAT‑style deep technical problem solving to resolve customer‑impacting issues

• Forward‑deployed, customer‑facing engineering to support deployments and escalations

• Hands‑on software development and automation that improves customer experience at scale

You will take ownership of the most complex, ambiguous, and high‑impact production challenges—especially those involving AWS infrastructure, Databricks workloads, and large‑scale data pipelines. You’ll work directly with customers to diagnose issues, guide them through critical moments, and ensure that insights from the field translate into durable improvements across our platform and products.

This is a hands‑on, high‑visibility role. You will lead technically during incidents, debug live systems, and write production‑grade code when it meaningfully enhances reliability, operability, and customer outcomes.

Your day to day

Production Operations & Incident Response

• Act as a senior technical escalation point during production incidents
• Lead real-time incident triage, mitigation, and recovery efforts
• Drive root cause analysis (RCA) with a focus on systemic, long-term fixes
• Identify recurring failure patterns and push for architectural or operational improvements
• Partner with Customer Success and Engineering to manage customer impact during incidents

Sustaining Engineering & Post‑Launch Ownership

• Own post-launch reliability, stability, and operational quality of core systems
• Investigate and resolve complex field issues and production defects
• Ensure fixes developed during incidents or customer escalations are up streamed into the core product
• Improve operational readiness of services through better runbooks, monitoring, and alerting
• Reduce operational toil by converting repeated manual work into automation

Forward Deployed / Customer‑Facing Engineering

• Engage directly with strategic customers to solve real-world, production-grade technical challenges
• Support complex deployments, integrations, and escalations in customer environments
• Act as a trusted technical partner to customers during high-impact issues
• Translate customer learnings into concrete product, platform, and operational improvements
• Contribute to reusable tools, playbooks, and best practices that accelerate future deployments

AWS & Databricks Technical Expertise

• Serve as a subject matter expert for AWS-hosted production systems
• Troubleshoot and resolve issues across:
  • AWS compute, storage, networking, IAM, and security
  • Databricks jobs, clusters, and Spark-based data pipelines
• Debug performance degradation, scalability issues, job failures, and data correctness problems
• Partner with platform and data teams to harden systems for reliability, scale, and operability

Software Development & Automation

• Write production-quality code to:
  • Automate operational workflows
  • Improve reliability and observability
  • Eliminate manual intervention and reduce incident frequency
• Contribute primarily in Python, with exposure to JVM-based systems as needed
• Review code with a strong emphasis on operability, resiliency, and maintainability
• Advocate for “build it so it can be operated” engineering standards

Technical Leadership & Collaboration

• Provide technical leadership without formal authority, influencing design and operational decisions
• Mentor engineers through pairing, reviews, and incident leadership
• Collaborate closely with Product, Engineering, Data, and Customer teams
• Operate effectively in high-pressure, ambiguous environments, especially during customer-impacting incidents

What you bring to the team 

• 10+ years of experience in software engineering, SRE, sustaining engineering, or production operations
• Deep hands-on experience operating production systems in AWS
• Strong experience troubleshooting Databricks and large-scale data platforms
• Proficiency in Python and experience building production services or tooling
• Strong understanding of:
  • Distributed systems
  • Incident management and RCA practices
  • Monitoring, alerting, and observability
  • CI/CD Pipelines that leverage Infrastructure as Code.
• Proven ability to own problems end-to-end, from detection to permanent resolution
• Excellent communication skills, especially during incidents and customer escalations
• Ability to work backward from customer impact to root cause across systems and codebases, delivering fixes in environments with minimal documentation.
• Strong instinct for operational risk, with the ability to proactively identify failure modes and harden systems before they impact customers.

What we would like to see, but not required: 

• Experience in healthcare, health insurance, or regulated data environments
• Familiarity with:
  • Kubernetes (EKS), EMR, Lambda
  • Spark internals
  • Snowflake or similar data warehouses

• Experience with FHIR, MDM systems, or entity resolution
• Prior experience in SWAT, escalation engineering, or tiger-team roles
• Experience contributing to or operating within SRE/on-call programs

Compensation: Compensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants.

What you’ll get in return:

• Unlimited paid time off – recharge when you need it
• Work from anywhere – flexibility to fit your life
• Comprehensive health coverage – multiple plan options to choose from
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here
• Home office setup allowance – one-time support to get you started
• Monthly cell phone allowance – stay connected with ease#LI-MS1

About the Role

The Site Reliability and Forward Deployed Engineer is an experienced individual contributor responsible for supporting production operations, incident response, and post‑launch reliability across the Abacus Insights platform.

This role combines:

• Production operations and reliability engineering
• Deep technical problem-solving during incidents and escalations
• Customer‑facing technical support for deployments and issues
• Hands‑on software development and automation

You will work on complex production issues involving AWS infrastructure, Databricks workloads, and data pipelines, partnering closely with senior engineers and platform teams. You will engage with customers during escalations and deployments and help translate learnings into product and operational improvements. This is a hands‑on role. You are expected to actively participate in incidents, debug live systems, and write production code that improves system reliability and operability, with guidance from senior technical leaders.

Your day to day

• Act as a technical escalation point during production incidents, leading real‑time triage, mitigation, and recovery efforts.
• Drive root cause analysis (RCA) and ensure follow‑up remediation and reliability improvements are completed and tracked.
• Support post‑launch reliability by investigating and resolving production defects and field‑reported issues.
• Partner closely with Engineering, Data, and Customer Success teams to support customers during high‑impact incidents and escalations.
• Improve operational readiness through better runbooks, monitoring, alerting, and incident response practices.
• Work directly with customers on complex deployments, integrations, and production troubleshooting in customer environments.
• Write production‑quality code (primarily Python) to automate operational workflows, improve observability, and reduce manual toil.
• Support and troubleshoot AWS‑ and Databricks‑based production systems, including performance, scalability, and data correctness issues.
• Capture learnings from incidents and customer engagements and translate them into reusable tools, documentation, and product improvements.

What you bring to the team

• 3 - 5 years of experience in software engineering, SRE, sustaining engineering, or production operations
• Hands‑on experience supporting production systems in AWS
• Experience troubleshooting large‑scale data platforms or Databricks
• Proficiency in Python and experience building or supporting production services or tooling
• Working knowledge of:
  • Distributed systems fundamentals
  • Incident response and RCA practices
  • Monitoring, alerting, and observability
  • CI/CD pipelines and Infrastructure as Code concepts
• Strong communication skills during incidents and customer interactions
• Ability to take ownership of issues through resolution with support and guidance
• Good operational judgment and willingness to learn how to proactively reduce risk

What we would like to see, but not required

• Experience in regulated or healthcare data environments
• Familiarity with Kubernetes (EKS), EMR, Lambda, Spark internals, Snowflake, Databricks or similar data warehouses
• Experience participating in on‑call or SRE programs
• Prior customer‑facing or escalation engineering experience

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Working Arrangements

• Standard hours: 9 hours/day, 5 working days
• Location: Onsite
• Shift: 1 PM - 10 PM local time

About the Role:
As a Senior AI Engineer, you will help architect, build and implement our AI platforms, working closely with data quality engineers, data/software engineers, platform engineers, DevOps, product owners and business.  You provide technical leadership for multiple, diverse, and geographically distributed teams. You will coach and guide teams to enable future success. Also be a partner with engineering managers, directors and VP on strategic initiatives and future business growth opportunities especially around AI and ensuring the engineering organization can scale to meet the need.

As a member of the engineering team, you are responsible for coaching, mentoring, and driving change to enable us to better deliver and innovate in an agile environment.

Your day to day:

• Help shape the direction of our applied AI areas and intelligence features in our products. Drive the deployment of state-of-the-art AI models and systems that directly impacts on the capabilities and performance of Abacus’s products and services (e.g., Abacus Agents, MCP, SQL and RAG agents and tools, etc.)
• Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains
• Design and implement ML/AI pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation, iteration and self-healing
• Work closely with cross-functional teams, including AI engineers, data engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction
• Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model and GenAI system performance
• Skillful at driving critical projects (e.g. AI and data engineering Innovation, Development Productivity and Benchmarking)
• Meaningful experience in the world of Data and AI
• Capable of credible customer interactions
• Mentoring development team members to ensure delivered solutions adhere to the software architecture strategy, coding standards, and established organizational policies and procedures
• Participating in software architectural discussions, influencing decisions, and collaborating with peers to maintain consistency across the organization
• Identifying people and process improvement strategies for the Agile/Scrum team(s), especially for AI projects/teams where innovation and iteration are critical
• Communicate organizational updates to ensure teams adhere to the established policies and procedures
• Ensure projects are completed on time and according to our quality standards
• Facilitates communication upward around architecture, design, and implementation objectives
• Proven experience in leading software development teams or projects
• Excellent knowledge of software development design, QA and test automation, and experience with agile development methodologies
• Demonstrated knowledge of Cloud Architecture, AI Architecture, Agents/Agentic systems, Massive Parallel Processing (MPP) compute frameworks for Data+AI platforms, Security, and MCP/API based services
• Good understanding of Incident Management, Configuration Management, Operational efficiency and Customer Escalation Management preferred. Can manage the balance of deliveries on our roadmap commitments while dealing with interruptions and client escalations
• Good experience with open source
• Coach and mentor software and AI developers, develop staff skills, provide continuous feedback 
• Has relentlessly high standards (is never satisfied with the status quo)
• Responsible for protecting, securing, and proper handling of all confidential data held by Abacus to ensure against unauthorized access, improper transmission, and/or unapproved disclosure of information that could result in harm to Abacus or our clients.

What you bring to the team:

• Minimum of 3 years of ML/AI engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML/AI research in academia will be considered as contributing qualification
• Minimum of 3 years of experience as a software developer at some point in career
• Minimum of 2 years of experience with Databricks, Mosaic AI Gateway and associated technologies in Databricks stack related to Data and AI engineering
• Strong track record of working with language modeling technologies and GenAI. This could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, evaluation benchmarks, Agents and Agentic workflows (e.g. orchestration, workflow management, observability, debugging), RAG, SQL Agents, MCP, etc.
• Proficiency in Python, TensorFlow/PyTorch, and scalable ML/AI architecture
• Ability to drive end-to-end model and system development, from research and prototyping to deployment and monitoring
• Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment
• Experience and good understanding of designing scalable, distributed systems for running small to medium scale data processing applications and services (10s – 100s of TBs of data)
• Possesses a level of breadth and depth of software and AI development experience that allows for influence and competence in technical discussions with internal and external stakeholders
• Solid understanding of roles adjacent to the software development (product management, project management, client delivery, operations etc.). Ability to adapt to these roles as defined at Abacus and work with others in these roles
• Proven record of success of driving and/or leading engineering teams/projects towards developing production grade systems supporting customers
• Nice to have experience with, but not required: Snowflake, FHIR, Healthcare Data exposure

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST