Careers

Skills Required

• Has owned end-to-end delivery of a consulting or technology project from kick-off through go-live — can walk through decisions, blockers, quality gates, and outcomes.
• Has prior experience of hands-on technical delivery of multiple projects in the capacity of developer and/ or technical lead of analytics and/ or application development projects.
• Has proficiency in multiple tools/ technologies for application development and business/ data analysis
• Has managed 2 or more concurrent projects simultaneously — can describe how prioritization, resource allocation, and conflict resolution were handled.
• Has tracked and managed a project budget: actuals vs. plan, burn rate, forecast to complete — in any tool.
• Can run a full sprint cycle independently — planning, grooming, review, retro — and demonstrate how velocity was tracked and course-corrected.
• Has managed a technical team’s delivery quality — code reviews, architecture alignment checks, or NFR validation — not just scheduled them.
• Familiar with CMMI Level 3 practice requirements — can list mandatory PM process outputs and explain their purpose and compliance criteria.
• Has owned a risk register with 10+ active items across one or more projects and can demonstrate how specific risks were tracked to resolution.

Roles & Responsibilities

• Own project planning across one or more concurrent engagements — scope baseline, WBS, milestones, resource plan, and sprint calendar.
• Run sprint ceremonies independently — planning, backlog grooming, sprint review, and retrospectives — and track velocity against delivery commitments.
• Track progress across all workstreams; identify and resolve slippage before it impacts milestones.
• Manage Project team allocation across engagements; maintain workload balance and delivery coverage.
• Own delivery quality standards across all technical workstreams — architecture alignment, code quality gates, NFR compliance, and performance benchmarks.
• Review and approve technical artifacts (design documents, data models, integration specs) for completeness and quality before development proceeds.
• Ensure QA and testing cycles are thorough and quality-verified before handoff to UAT — not just scheduled, but validated.
• Identify and resolve technical risks and quality gaps proactively, before they surface in UAT or production.
• Own all CMMI Level 3 or higher process compliance across planning, execution, monitoring, and closure phases.
• Maintain mandatory process artifacts: plans, risk logs, status reports, change logs, and meeting minutes.
• Run internal delivery governance — milestone reviews, delivery sign-offs, change control board.
• Participate in process audits; identify and report deviations; drive corrective actions to closure.
• Reinforce process discipline within the delivery team without impeding velocity.
• Own project budget tracking across one or more engagements: actuals vs. plan, burn rate, and forecast to complete.
• Manage resource allocation and cost per project; flag budget risks before they breach thresholds.
• Coordinate with delivery leadership on staffing, onboarding, and off-boarding across concurrent engagements.
• Own the risk and issue register across all assigned engagements — log, track, escalate, and close with urgency.
• Manage cross-project dependencies and resource conflicts.
• Surface blockers proactively; resolve without waiting for milestone slippage to force action.

Other Good-to-Have exposure

• Oil & Gas: upstream, midstream, or downstream.
• Polymers, specialty chemicals, or petrochemicals.
• Energy trading or utilities.
• Materials manufacturing or industrial processing.
• PMP, PRINCE2, PMI-ACP, or SAFe certification.
• Exposure to SAP, Oracle, or enterprise platform delivery programs.
• Experience working in CMMI Level 3 or higher appraised organizations.
• Background in data, systems integration, or digital transformation programs.
• Prior experience as Scrum Master or Agile delivery lead.

Skills Required

• Excellent communication and influencing skills –able to set and land standards across pods without formal reporting authority.
• Deep hands-on experience with observability stacks (e.g., Prometheus, Grafana, ELK/OpenSearch, Datadog) – designing dashboards, alerts, and golden signals.
• Proven experience defining and operationalizing SLIs, SLOs, and error budgets, and using them to drive engineering and release decisions.
• Strong background in incident management – oncall design, escalation paths, severity classification, and blameless postmortems.
• Hands-on expertise with Kubernetes, container orchestration, and cloud-native infrastructure (AWS, Azure, or GCP).
• Infrastructure as Code and automation experience (Terraform, Ansible, Helm, or equivalent) with a strong toil-reduction mindset.
• Proficient in scripting/programming for automation and tooling (Python, Go, or Shell).
• Experience with CI/CD platforms and release engineering (Jenkins, GitLab CI, ArgoCD, or similar).
• Working knowledge of capacity planning, performance tuning, and cost optimization for production systems.
• Familiarity with chaos engineering, disaster recovery, and multiregion resilience practices.
• Ability to mentor engineers across multiple pods, run guild syncs, and maintain shared runbooks, standards, and playbooks.
• Proven ability to work cross-functionally with Architecture, DevOps & Infra, and Delivery leadership

Roles & Responsibilities

• Own the SRE guild charter – define reliability standards, tooling, and best practices applied consistently across all Dev Factory pods.
• Define and govern SLIs, SLOs, and error budgets for key services in partnership with pod leads and architects.
• Lead the guild’s incident management practice – on-call rotations, escalation paths, and blameless postmortems; act as senior escalation point for critical production incidents.
• Drive observability strategy across the organization, ensuring pods have consistent monitoring, alerting, and logging coverage.
• Champion automation and toil reduction, identifying repetitive operational work across pods and driving it toward self-service or automated remediation.
• Partner with the DevOps & Infra guild to align infrastructure, deployment, and reliability practices, and flag capacity or staffing gaps to guild and delivery leadership.
• Mentor and upskill SREs and DevOps engineers embedded in pods, running guild-wide knowledge-sharing sessions and maintaining shared runbooks.
• Contribute to hiring, onboarding, and career pathing for the SRE discipline across the delivery organization.
• Collaborate with the Architecture & Design guild on non-functional requirements – scalability, fault tolerance, and disaster recovery – during solution design.
• Track and report guild health metrics (incident trends, MTTR, SLO attainment, automation coverage) to Dev Factory leadership.
• Stay current on SRE tooling and industry practices, evaluating and introducing new technologies where they improve reliability or reduce operational cost

Skills Required

• Technical Fluency Working knowledge and intellectual curiosity regarding modern AI paradigms, including Agentic AI, AI agents, semantic context matching, data lakes/lakehouses, and large-scale analytics platforms.
• Communication & Presence Exceptional command over written and spoken English, paired with dynamic public speaking, presentation, and C-suite negotiation skills.
• Drive & Motivation Highly self-motivated, aggressive hunter mindset with an innate urge to excel and set benchmarks in enterprise sales.
• Process Discipline Highly organized, disciplined in CRM data upkeep, and professional in handling complex, multi-stakeholder problem-solving scenarios.
• Target Sectors Government, Public Sector Undertakings (PSUs), Oil & Gas, Refineries, and Large Enterprise

Nice to Have

• Enterprise & Strategic Account Leadership
  • Drive end-to-end sales campaigns and large deals within Government, PSUs, Oil & Gas, and Refineries.
  • Manage complex, multi-layered sales cycles involving technical evaluations, proof-of-concepts (PoCs), security compliance reviews, and tender/RFP processes.
  • Own key account strategies, mapping organizational hierarchies from technical stakeholders to C-suite and board-level executives.
• Domain & Technological Evangelism
  • Articulate and demonstrate the business value of mcube™, highlighting advanced concepts such as Agentic AI, autonomous AI agents, knowledge graphs, semantic context matching, and enterprise data lakehouse infrastructure.
  • Translate complex technical capabilities into clear, high-impact business outcomes for government and industrial leaders.
• Account-Based Engagement & Planning
  • Design and execute structured account-based marketing and sales workshops, customer contact sessions, and executive alignment briefings.
  • Create bespoke engagement plans focused on specific customer pain points, digital transformation metrics, and measurable ROI.
• Sales Governance & Execution Excellence
  • Maintain pristine data hygiene, pipeline transparency, and accurate forecasting within the enterprise CRM system.
  • Apply a structured, methodical problem-solving approach to navigate enterprise procurement roadblocks, legal terms, and partner ecosystems.

Skills Required

• System Requirement analysis (use cases, user stories etc.). UI/UX
  prototyping. Domain Modelling. Functional decomposition. Design
  Thinking desirable.
• Experienced in design using Object-Oriented (OOAD) using UML,
  Domain Driven Design (DDD), Design Patterns & Data Modelling
  (ERD etc.). Separation of concern. System Thinking.
• Must have strong experience in Object Oriented Programming (OOP)
  using Python, TypeScript or Java. Vibe Coding and verification.
• Hands-on experience in designing & developing end to end scalable
  solutions etc.
• Must have implemented cloud-native Microservices.
• Strong hands-on project experience in Solution Architecture
  covering the functional, application, technical, deployment, security
  and physical aspects of architecture. C4 model.
• Must have string understanding of core software engineering &
  architectural best practices
• Excellent communication skills (for effective communication with
  stakeholders)
• Scalability & Resilience: Deep knowledge of high-concurrency
  systems, distributed systems, clusters, fault tolerance, circuit
  breakers, and multi-region disaster recovery strategies.
• Test driven development (TDD)
• Implemented or used the CI/CD or DevOps platform technologies
  e.g., Docker, Kubernetes, Git, Jenkins, Artifactory etc.

Nice to Have

• Experienced in Agile Methodology, Project Planning & Task
  allocation to the team members. Should have practical experience in
  effort estimation for projects & deliver customer projects with
  ownership.
• Guide the engineering teams, preventing “architectural drift” over
  time. Moving beyond code reviews to mentoring engineers and
  junior architects on system thinking and systemic problem-solving.
  Serving as the point of escalation for catastrophic system failures.
• Cloud experience in any public cloud platform e.g., AWS, Azure, GCP
  etc.
• TOGAF certification.
• Desirable experience in Data Lakes, Data Engineering, Data
  Management, ETL, Analytics, Machine Learning & AI technologies
  e.g., GenAI, LLMs, AI Agents, Sklearn, Graphs & Charting tools.
  Should understands data analytics, data warehouses, data
  engineering, data science, reporting and data visualization.
• Proven ability to work cross-functionally.

Key Responsibilities

• End to end solution architecture, design, development & delivery
  for customer use cases
• Provide top-quality solution design (high level & low level) for all
  layers e.g., Frontend, APIs / Services, Database and Integration.
• Design applications to execute on Cloud Based (AWS) or Kubernetes
  platforms
• Lead the development team
• Provide support in defining the scope and sizing of work
• Engage with clients to understand strategic requirements
• Responsible for translating business requirements into technology
  solutions aligned to our products
• Work with domain experts to put together a delivery plan with and
  stay on track
• Utilize Microservices technologies to design, develop, and evolve
  scalable and fault-tolerant distributed platforms
• Organize all meetings with customers and ensure prompt resolution
  of gaps and roadblocks
• Real time and bulk data processing using ETLs into ElasticSeach,
  PostgreSQL, MariaDB
• Stay current on latest technology to ensure maximum ROI for clients
• Technical mentorship for the team in design and development

Skills Required

• 6 – 10 years of product management experience, with ownership of customer-facing platforms or APIs.
• 3+ years shipping and operating AI/ML-powered products in production.
• Strong understanding of LLM-based systems, RAG architectures, and AI ecosystem.
• Knowledge of Agent development frameworks and MCP.
• Ability to reason about trade-offs between accuracy, latency, cost, and UX.
• Comfortable reviewing prompts, experiments, dashboards, and system metrics.
• Strong communication skills in highly technical and ambiguous domains.

Nice to Have

• Experience with semantic technologies such as knowledge graphs, ontologies, or semantic data models.
• Experience building AI platforms for enterprise customers.
• Familiarity with AI governance, compliance, or regulated environments.
• Exposure to UX patterns for AI-driven workflows.

Key Responsibilities

• Own the vision, roadmap, and success metrics for the AI platform.
• Define core platform capabilities.
• Enable customer and internal teams to build AI use cases using scalable platform primitives.
• Prototype AI workflows and reference implementations to validate new capabilities.
• Define and track KPIs for AI quality, latency, reliability, cost, and adoption.
• Embed enterprise-grade guardrails for security, privacy, and safe AI usage.
• Influence (not solely own) decisions e.g. model selection, buy vs build, risk trade-offs, etc
• Act as the product interface across engineering, ML, security and go-to-market teams.

Skills Required

• Expert knowledge of data science algorithms, methodologies, and end-to-end lifecycle (AI/ML/GenAI), MLOps and post deployment service of AI models
• Strong comprehension of complex Oil & Gas and downstream Petrochemical industries problem.
• Exceptional articulation skills to communicate technical concepts clearly to both technical and business stakeholders.
• Advanced analytical skills for strategic problem-solving and actionable insight generation.

• Exposure to cloud platforms (AWS/Azure/GCP), DevOps, deployment and scaling frameworks
• Experience in leading agile teams and agile methodology.
• Familiarity with data visualization tools (e.g., Tableau, Power BI).
• Understanding of data engineering principles and big data.

Roles & Responsibilities

• Lead data science efforts (AI, ML, GenAI, optimization) for multiple client engagements in n Oil & Gas and downstream Petrochemical industries.
• Manage end-to-end Data Science project lifecycle from problem comprehension, analytical solution development to final delivery.
• Act as primary point of contact for client interactions, presentations, and requirement elicitation.
• Guide teams on advanced data science techniques ensuring alignment with business objectives.
• Collaborate cross-functionally with domain experts, business stakeholders, and technical teams to deliver robust analytical solutions.

Other Information