Become a Bug Bounty Hunter.

NLP Engineers build production language systems — Indic-language models, automatic speech recognition (ASR) and synthesis (TTS), document understanding for enterprise paperwork, IVR and voice-bot stacks for Indian customer support, named-entity recognition and information extraction, and the increasingly common multimodal pipelines that fuse text with vision and speech. The work blends applied research, production engineering, and dataset craft: you train and fine-tune transformer models for low-resource Indic languages, curate parallel corpora and labeled datasets, optimize inference for cost, debug failure modes that only show up in code-mixed Hindi-English speech or in handwritten Tamil documents, and own quality SLOs that mix accuracy, latency, and fairness across 22 official Indian languages. In India through 2026, NLP is one of the highest-impact applied-AI specializations because the global English-first NLP literature transfers poorly to Indic languages — concentrated demand sits at AI-native startups (Sarvam AI, Krutrim, Ola Krutrim, Yellow.ai), the public-good NLP groups at AI4Bharat (IIT-Madras) and Bhashini (Government of India), enterprise SaaS (Freshworks, Zoho ZIA, Postman, Verloop, Haptik), fintech (Razorpay, Cred, Paytm, M2P, IDfy), and the GCCs of Microsoft, Google, Adobe, and Amazon.

Power BI Developers design, build, and maintain the BI layer that turns raw enterprise data into decision-grade dashboards for finance, operations, sales, and supply-chain teams. The core loop is: connecting heterogeneous sources via Power Query (M language), modelling star schemas with fact and dimension tables, writing DAX measures and calculated columns for time-intelligence and KPI logic, publishing to Power BI Service workspaces, enforcing row-level security policies, and tuning slow reports by reducing visual-query counts and optimising DirectQuery folding. In India, this role is the Microsoft-stack alternative to Tableau development — deeply embedded in the M365-heavy enterprises: TCS, Infosys Nia practice, Wipro's Microsoft Business Applications unit, Mahindra Group, Tata Group digital, L&T Infotech (LTIMindtree), HCL, and every banking captive running Azure Synapse or Fabric. Demand spiked in 2024-2026 as Microsoft Fabric (Lakehouse, Semantic Model, Dataflows Gen2) expanded the Power BI surface area and pushed experienced developers into the ₹18-40L band.

Keep production systems fast, available, and observable for millions of users — by writing software that automates operations, runs capacity planning, designs SLOs and error budgets, and owns the on-call rotation for critical services. The role sits between software engineering and operations: you write Go / Python / Rust code, build reliability tooling, design distributed systems for resilience, run incident response, and push back on product launches that risk SLOs. In India, SRE is a premium specialization concentrated at FAANG-IN (Google SRE Bengaluru, Amazon, Microsoft IDC, Netflix India), product unicorns (Razorpay, Flipkart, Swiggy, Dream11, PhonePe, Zerodha), and the GCCs of high-traffic US firms (Uber, LinkedIn, Atlassian, GitHub, Cloudflare, Stripe). The work overlaps with DevOps but skews more toward software engineering: reliability is a product, not a process. Senior SRE pay in India sits at the very top of the technology bracket, often above equivalent SDE-3 backend roles.

Build and operate the internal developer platform — the CI/CD pipelines, Kubernetes clusters, service mesh, secrets management, observability stack, and IaC modules — that every other engineer in the company ships on. Platform engineers turn raw cloud (AWS/GCP/Azure) into a paved road: a developer pushes code, the platform takes it from commit to canary to production with logs, metrics, and rollback baked in. In India, the role is concentrated at product unicorns (Razorpay, Zerodha, CRED, PhonePe, Swiggy), GCCs of global firms (Microsoft, Atlassian, Stripe, Walmart Global Tech), and SaaS companies scaling past 200 engineers — typically the point at which a dedicated platform team starts paying for itself in shipping velocity.

Solutions Architects are the customer-facing technical role that bridges what a product can do and what a customer actually needs. They design end-to-end deployments, integrations, and migrations on behalf of the customer's engineering team — sizing infrastructure, mapping data flows, picking the right product modules, drafting reference architectures, and partnering with sales and customer-success to win and expand accounts. The role is genuinely hybrid: it requires deep technical depth (cloud, networking, security, distributed systems) and high verbal craft (workshops, executive presentations, written design docs that survive procurement and security review). In India through 2026, Solutions Architect is one of the highest-paid customer-facing technical roles, concentrated at the GCCs of cloud vendors (AWS India, Microsoft Azure India, Google Cloud India, Oracle, IBM), enterprise SaaS companies (Salesforce India, ServiceNow, Snowflake, Databricks, MongoDB, Confluent), B2B Indian product companies (Freshworks, Postman, Atlan, Hasura, Chargebee), and the systems-integrator giants (TCS, Infosys, Wipro, Accenture) where the role sits closer to delivery. Top-tier Solutions Architects in India routinely cross ₹1Cr total comp by L6+ and the role is a common path into VP-Engineering and Field-CTO seats.

Prompt Engineers design, evaluate, and ship LLM-powered features — system prompts, RAG flows, agent orchestration, structured-output schemas, and the eval harnesses that prove a prompt is actually better. The role sits between product, applied ML, and software engineering: you write prompts the way other engineers write code, run cost-quality-latency trade-off experiments, instrument grader pipelines, and own the part of the product that the LLM actually 'speaks.' In India through 2026, the role is one of the fastest-growing AI hires — concentrated at AI-native startups (Sarvam AI, Krutrim, Ola Krutrim, Atlan, Yellow.ai), product SaaS shops with a serious AI feature surface (Freshworks, Postman, Chargebee, Whatfix, Zoho ZIA), fintechs (Razorpay, Cred, Paytm), and the GCCs of Microsoft, Google, Adobe, and Salesforce. The salary band is unusually wide because the title is new and JDs vary from 'wrote one ChatGPT integration' to 'owns the eval harness for a frontier model.' Sarvam AI made several public crore-level offers to senior prompt and LLM engineers in 2025.

Antique dealers in India source, authenticate, restore, and sell objects typically over 100 years old — furniture, silver, bronzes, paintings, textiles, coins, and ceramics — through physical galleries, auction consignments (Saffronart, AstaGuru, Pundole's), and private client sales. The trade is centred in Chor Bazaar (Mumbai), Sundar Nagar and Khan Market (Delhi), Mattancherry antique row (Kochi), and Pondicherry's French Quarter. Income is expertise-driven, not scale-driven: a dealer who can distinguish a Chola bronze from a later cast, read hallmarks on colonial silver, or date a Bidriware box from its alloy composition commands a premium that no catalogue can replicate. The AMASR Act 1972 and India Customs regulations prohibit export of any antiquity (object over 100 years old) without a Government of India permit — and most never get one. Every serious dealer must understand these legal boundaries before moving a single piece across state lines for a corporate client.

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Ethical hackers (penetration testers) are hired to break systems before adversaries do. They scope engagements, conduct structured attack simulations — network, web app, mobile, cloud, social engineering — and deliver reproducible proof-of-concept reports with remediation guidance. In India, the role spans consulting firms (Bishop Fox India, Lucideus/SAFE Security, NetSPI, NotSoSecure), in-house red teams at Razorpay, CRED, Swiggy, Flipkart, and major PSU banks, and independent bug-bounty hunters on HackerOne and Bugcrowd. Unlike defensive security, ethical hackers must think offensively on demand: simulating APT lateral movement, chaining zero-days, and writing custom exploits — all under a signed rules-of-engagement document that defines the legal boundary.

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Volcanologists study active, dormant, and extinct volcanoes through field observation, geochemical sampling, remote sensing, and geophysical monitoring to understand eruptive processes and assess hazards. In India the domain is anchored by Barren Island (Bay of Bengal, India's only confirmed active volcano, last major eruption 2017-18) and Narcondam Island, with institutional homes at the Geological Survey of India (GSI), the National Centre for Polar and Ocean Research (NCPOR — Antarctic volcanism at Deception Island), and the National Centre for Seismology (NCS) under MoES. Indian volcanologists collaborate with USGS Volcano Hazards Program, IAVCEI, and the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for monitoring methodology and capacity building. Career paths demand M.Sc. in Geology (igneous petrology, geochemistry) followed by a PhD specialising in volcanology — genuine niche, tiny hiring pool, high international mobility.

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A full-stack builder who ships both the smart-contract layer (Solidity on EVM chains — Ethereum, Polygon, Arbitrum, Base) and the dApp frontend that users actually touch (React / Next.js with wagmi / viem / ethers.js, WalletConnect, MetaMask). Unlike a pure protocol engineer who focuses on DeFi architecture and audit, a Web3 Developer owns the entire user-facing product: wallet connection flows, NFT minting UIs, on-chain data indexing via The Graph, IPFS / Arweave asset storage, and gas-cost UX. In India, the role is concentrated at crypto exchanges and product companies (CoinDCX, CoinSwitch, Biconomy, Push Protocol, Lens Protocol), Polygon's ecosystem of DApp and tooling teams, and a substantial remote-payroll layer where Indian developers invoice US / EU Web3 startups and DAOs directly in USDC or stablecoins. Entry requires fluency in both Solidity and a modern JS framework; senior roles demand end-to-end ownership from contract security to frontend performance.

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Generative AI Engineers build and ship systems that produce images, text, audio, and video — integrating APIs like OpenAI's DALL-E 3, Stability AI's SDXL, and Anthropic's Claude into product features, running Stable Diffusion inference pipelines on AWS/GCP GPUs, fine-tuning ControlNet and LoRA adapters on proprietary datasets, and orchestrating multi-modal generation workflows with quality and safety guardrails. In India through 2026, the role is concentrated at image-tech companies (Glance, InMobi, Meesho's catalog team), conversational-AI startups (Yellow.ai, Haptik, Niki AI), design-automation tools (Adobe Firefly India team), and the GCCs of Microsoft, Adobe, and Nvidia — with a fast-growing fringe of Stable-Diffusion startups building for e-commerce product shots, ad-creative automation, and Indic-language content generation. The role sits between classical ML engineering and software engineering: you own the model pipelines and the API integrations that make generation reliable, fast, and cost-efficient at product scale — not the fundamental model research.

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