Full stack Observability Engineer

Position Overview 

The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems. 

Responsibilities 

• Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms 
• Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning 
• Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection 
• Deploy, maintain and monitor containerized ML workloads 
• Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows 
• Implement AI-driven data validation, schema and concept drift detection and metadata management. 
• Establish governance frameworks for AI systems, including bias detection, explainability, and auditability 
• Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention 
• Develop automated test suites for model performance, regression, edge cases and bias validation 
• Monitor model KPIs (accuracy, precision, recall, latency, calibration) 
• Ensure reproducability of experiments and production models 
• Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption 

Qualifications 

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field 
• 5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering 
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure 
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn 

Job Summary

We are looking for an experienced Observability Engineer with strong expertise in ThousandEyes, Splunk, database technologies, and Python automation. The candidate will be responsible for monitoring application, network, and infrastructure performance, identifying issues, and developing automation solutions to improve system visibility, reliability, and operational efficiency.

Required Skills

• Observability
• ThousandEyes / Cisco ThousandEyes
• Splunk
• OracleDB
• MongoDB
• SQL
• Python Automation

Roles & Responsibilities

• Implement and support observability and monitoring solutions across applications, networks, and infrastructure.
• Work with ThousandEyes for network and digital experience monitoring.
• Configure and maintain monitoring dashboards, alerts, and performance metrics.
• Use Splunk for log analysis, monitoring, troubleshooting, and reporting.
• Work with OracleDB, MongoDB, and SQL for data analysis and troubleshooting.
• Develop Python scripts for monitoring and operational automation.
• Analyze performance issues and identify root causes across applications and infrastructure.
• Collaborate with application, infrastructure, and network teams to resolve incidents.
• Improve monitoring, alerting, and automation processes.
• Prepare performance and monitoring reports and provide actionable insights.

Mandatory Skills

• 7+ years of relevant experience
• Strong experience in Observability / Monitoring
• Hands-on experience with ThousandEyes
• Splunk
• Python Automation
• SQL
• OracleDB / MongoDB

Strong Lead AI Engineer Profile with agentic systems architecture expertise

2

Mandatory (Experience 1): Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems

3

Mandatory (Tech skill 1): Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), with experience debugging framework internals

4

Mandatory (Tech skill 2): Must have direct SDK experience with Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder

5

Mandatory (Tech skill 3): Must have Python mastery — production-quality code, type annotations, unit and integration tests, packaging, and performance profiling

6

Mandatory (Tech skill 4): Must have RAG pipeline depth — embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses

7

Mandatory (Tech skill 5): Must have cloud deployment experience with AWS, Azure, or GCP; Docker, Kubernetes, IaC basics (Terraform or CDK), and CI/CD pipelines

8

Mandatory (Tech skill 6): Must have agent observability experience — LangSmith, Helicone, or equivalent — with ability to diagnose latency, cost, and quality issues in production traces

9

Mandatory (Tech skill 8) : Must have owned full sub-system designs — agent topology, data flows, API contracts, failure handling — for a bounded scope, and built multi-agent graphs, tool orchestration, retrieval, and memory systems.

10

Mandatory (Tech skill 7): Must have track record of shipping 2+ agentic or ML systems to production — not just proof-of-concepts — with documented performance benchmarks

11

Mandatory (Communication): Must be able to write crisp component specifications and communicate architectural trade-offs to both engineers and non-technical stakeholders

12

Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well upto 6 days a month

Job Summary

We are looking for a Senior Observability Engineer with strong expertise in ThousandEyes, Splunk, and Monitoring & Observability Engineering. The candidate should have experience implementing and enhancing monitoring solutions, along with basic Python automation scripting.

Primary Skills

• ThousandEyes
• Splunk
• Monitoring & Observability Engineering
• Oracle Database
• SQL
• MongoDB
• Python Automation

Key Responsibilities

• Implement, configure, and enhance enterprise monitoring and observability solutions.
• Work extensively with ThousandEyes for network and application performance monitoring.
• Develop and maintain monitoring dashboards, alerts, and reports using Splunk.
• Monitor application, infrastructure, network, and database performance.
• Work with Oracle Database, SQL, and MongoDB for monitoring and troubleshooting.
• Develop basic Python automation scripts to improve monitoring and operational efficiency.
• Analyze performance issues and support troubleshooting and root cause analysis.
• Collaborate with application, infrastructure, network, and database teams to resolve observability-related issues.
• Continuously improve monitoring coverage, alerting, and operational processes.

Secondary Skills

• GenAI Concepts
• SaaS Architecture Concepts
• Cloud Application Architecture

Ideal Candidate Profile

• 7+ years of experience in Observability / Monitoring Engineering.
• Strong hands-on experience with ThousandEyes and Splunk.
• Good understanding of databases including Oracle, SQL, and MongoDB.
• Basic hands-on experience with Python automation.
• Understanding of application, infrastructure, and network monitoring.
• Exposure to GenAI, SaaS, or Cloud Application Architecture is an added advantage.

Job Description

We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.

Responsibilities

• Design, deploy, and manage Azure cloud infrastructure and services.
• Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
• Configure dashboards, alerts, health rules, and monitoring metrics.
• Perform log analysis, troubleshooting, and root-cause analysis for production issues.
• Implement observability solutions for applications, cloud infrastructure, and services.
• Automate monitoring and operational activities using scripting.
• Support incident, problem, and change management processes.
• Collaborate with development, DevOps, and SRE teams to improve system reliability.
• Maintain monitoring standards, documentation, and operational procedures.

Primary Skills

• Microsoft Azure
• Splunk
• Grafana
• AppDynamics
• Cloud Monitoring & Observability
• Application Performance Monitoring (APM)
• Log Analysis & Troubleshooting

Secondary Skills

• Azure Monitor / Log Analytics
• Azure VMs, Storage, Networking
• Linux
• Python / PowerShell / Shell Scripting
• CI/CD
• Git
• ITIL / ServiceNow

Job Description

We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.

Responsibilities

• Design, deploy, and manage Azure cloud infrastructure and services.
• Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
• Configure dashboards, alerts, health rules, and monitoring metrics.
• Perform log analysis, troubleshooting, and root-cause analysis for production issues.
• Implement observability solutions for applications, cloud infrastructure, and services.
• Automate monitoring and operational activities using scripting.
• Support incident, problem, and change management processes.
• Collaborate with development, DevOps, and SRE teams to improve system reliability.
• Maintain monitoring standards, documentation, and operational procedures.

Primary Skills

• Microsoft Azure
• Splunk
• Grafana
• AppDynamics
• Cloud Monitoring & Observability
• Application Performance Monitoring (APM)
• Log Analysis & Troubleshooting

Secondary Skills

• Azure Monitor / Log Analytics
• Azure VMs, Storage, Networking
• Linux
• Python / PowerShell / Shell Scripting
• CI/CD
• Git
• ITIL / ServiceNow

Job Summary:

We are looking for a Senior SRE/DevOps Engineer with strong experience in site reliability, automation, monitoring, observability, and production support. The candidate will be responsible for ensuring the reliability, availability, security, and performance of enterprise platforms.

Key Responsibilities:

• Own reliability, availability, security, and performance of enterprise browser platforms.
• Manage access and identity controls, Group Policy, and SAML/SSO integrations.
• Handle CI/CD deployments, configuration management, monitoring, and health checks.
• Develop automation and operational workflows using Python and Bash.
• Perform performance monitoring and production troubleshooting.
• Implement and maintain observability frameworks.
• Work with monitoring tools such as Datadog, Splunk, Dynatrace, Prometheus, and Grafana.
• Participate in incident management, RCA, and continuous improvement activities.
• Support highly available production environments in a 24/7 shift model.
• Collaborate with application, infrastructure, security, and operations teams.

Mandatory Skills:

• 10+ years of experience in SRE / DevOps.
• Strong hands-on experience in Python and Bash scripting.
• Experience with CI/CD and configuration management.
• Strong knowledge of monitoring and observability.
• Hands-on experience with Datadog, Splunk, Dynatrace, Prometheus, or Grafana.
• Experience with SAML/SSO, Identity & Access Management, and Group Policy.
• Banking domain experience.

• Business: Immerse in operations until you think like an insider.Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.
• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.
• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.
• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.
• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.
• Scale:  Design  complex  multi-component systems  end-to-end,  evaluate architectural options for large initiatives across teams, guide technical decisions or your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

What You Bring

• Bachelor’s degree in computer science, Software Engineering, or related field with 7+ years of relevant professional experience.
• Deep production experience with Python and JavaScript/TypeScript across backend and frontend, with demonstrated ability to work comfortably across the full stack.
• Strong experience with modern frontend frameworks (such as Next.js or React) and backend API development.
• Extensive experience with cloud platforms (AWS preferred; Azure or GCP also valued), including infrastructure-as-code tools (such as CloudFormation or Terraform).
• Deep Working knowledge of multiple database paradigms, including relational databases (such as PostgreSQL), document databases, and key-value stores (such as Redis), with the ability to select the right storage technology for each problem.
• Strong experience with CI/CD pipelines (such as GitHub Actions), containerisation, and production deployment strategies.
• Demonstrable fluency with AI coding tools (such as Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on AI-augmented development practices.
• Hands-on experience architecting production generative AI applications (LLM integrations, vector databases, RAG systems, evaluation pipelines) is essential.
• Experience leading technical initiatives across multiple teams, mentoring engineers, and establishing engineering practices is required.
• Experience navigating ambiguous problem spaces, working directly with business stakeholders and end users, and shipping working solutions rapidly is required.
• Experience in an embedded, forward-deployed, or consulting-style engineering model is a strong plus.

• Must have exceptional communication skills and demonstrated ability to influence at senior levels. This role requires comfort leading across ambiguous environments, building trust-based relationships with commercial stakeholders at all levels, developing junior and mid-level engineers, and making strategic decisions that balance delivery speed with architectural integrity. You will shape engineering practices across your area and be expected to lead multi-team initiatives.

Position Overview

We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and

maintain end-to-end software solutions spanning web platforms, desktop applications, and

autonomous AI agents capable of interacting with and controlling these software systems.

The ideal candidate will bridge traditional engineering software with cutting-edge artificial

intelligence to automate data processing and enhance operational decision-making. While

not strictly required, a background or strong interest in the energy sector—specifically

drilling and completion operations—is highly desirable.

Key Responsibilities

• Full Stack Development: Design, develop, and deploy robust web applications and

native desktop software utilized by engineering and operational teams.

• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-

driven workflows capable of interpreting data, executing commands, and safely

controlling desktop and web-based software.

• Workflow Automation: Translate complex workflows into intuitive software features

and autonomous agent actions, minimizing manual data entry and operational

bottlenecks.

• Data Integration: Handle high-frequency data streams and integrate them seamlessly

into user interfaces and backend AI models.

• Architecture & Scalability: Ensure high performance, security, and scalability across

cloud infrastructure (AWS/Azure), local desktop environments, and potential edge

computing setups.

• Cross-Functional Collaboration: Work closely with domain experts and end-users to

translate field challenges into technical product requirements.

Required Qualifications & Experience

• Experience: Minimum of 5 years of professional software development experience,

with a proven track record of delivering production-ready web and desktop

applications.

• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at

least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend

frameworks (React, Angular, or Vue.js), Node.js, and desktop application development

(Electron, WPF, Qt, or Tauri).

• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs

(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,

AutoGPT, or custom agent architectures.

• Automation & UI Control: Expertise in software control mechanisms using tools like

Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to

allow AI agents to navigate software.

• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud

platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.

Preferred Qualifications (Strong Plus)

• Industry Domain Expertise: Prior hands-on development experience within the oil and

gas sector, specifically focused on drilling, completions, rig operations, or subsurface

engineering software.

• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and

time-series databases.

• Experience deploying AI models and agents in edge or low-connectivity environments

(such as offshore rigs or remote drilling sites).

• Familiarity with safety-critical software design and cybersecurity standards in

industrial control systems (ICS/SCADA).

• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.

Position: Senior/Lead Full Stack Engineer – Gen AI / Agentic AI

Experience: 7+ Years

Employment: Permanent Position

Location: Banglore / Hyderabad

Job Summary

We are looking for a Senior/Lead Full Stack Engineer – Gen AI / Agentic AI with strong hands-on experience in Python, React.js, MongoDB, Java/Spring Boot and Generative AI/Agentic AI.

The candidate should have experience designing and developing scalable enterprise applications and implementing production-grade LLM, RAG, AI Agent and multi-agent solutions.

Key Responsibilities

• Design, develop and maintain scalable full-stack applications using Python, React.js, MongoDB and Java/Spring Boot.
• Build production-grade Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
• Develop RAG pipelines, AI agents, tool calling, memory management, planning and agent orchestration.
• Work with LangChain, LangGraph, MCP, vector databases and semantic search.
• Develop Python-based APIs, microservices and asynchronous applications using FastAPI/Flask/Django.
• Build REST APIs and event-driven microservices with focus on scalability, performance and resilience.
• Integrate LLMs, embeddings, vector stores and external enterprise tools/services.
• Implement prompt engineering, LLM evaluation, guardrails and AI observability.
• Develop responsive front-end applications using React.js.
• Work with MongoDB, SQL and hybrid data models.
• Implement CI/CD pipelines and support cloud/OCP deployments.
• Follow secure coding, testing, code quality and performance best practices.
• Participate in architecture, technical design, code reviews and mentoring of team members.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.

Mandatory Skills

1. Python
2. React.js
3. Gen AI / Agentic AI
4. RAG + LLM
5. LangChain / LangGraph
6. MongoDB
7. Java + Spring Boot
8. REST APIs / Microservices
9. Vector Databases / Embeddings
10. MCP / AI Agent orchestration

Good to Have

• FastAPI / Flask / Django
• Kafka / Solace
• Docker / Kubernetes
• AWS / Azure / GCP / OCP
• CI/CD – Jenkins / GitHub Actions
• LLMOps / AI evaluation / observability
• ELK / Grafana / Splunk / AppDynamics
• SQL / NoSQL
• Agile/Scrum